# Patent

## Title
Methods and systems for digitally counting features on arrays

## Abstract

Methods, systems and platforms for digital imaging of multiple regions of an array, and detection and counting of the labeled features thereon, are described.

## Background
CROSS-REFERENCE
This application claims the benefit of U.S. Provisional Application No. 61/887,853, filed Oct. 7, 2013, which application is incorporated herein by reference.


SEQUENCE LISTING
The instant application contains a Sequence Listing which has been submitted electronically in ASCII format and is hereby incorporated by reference in its entirety. Said ASCII copy, created on Nov. 5, 2014, is named 41977-711.201_SL.txt and is 255,804 bytes in size.
BACKGROUND OF THE INVENTION
Array technologies have been widely used in biomedical studies for the detection of biomolecules and profiling of gene expression levels, etc. Arrays are typically comprised of immobilized probes which can bind to or hybridize with target molecules in a sample. Detection of binding or hybridization events is often achieved through the use of optical labels (e.g. fluorophores) and scanning or imaging techniques (e.g. fluorescence scanning or imaging). A feature on an array is a small region of immobilized probes that are specific for a given target molecule, e.g. probes that hybridize to specific DNA or RNA sequences. Identifying the pattern of labeled features on a hybridized array thus provides information about specific molecules, e.g. DNA or RNA molecules in the sample, which in turn can provide valuable data in biomedical studies. Two important engineering requirements for providing high quality, quantitative data for biomedical investigations are (i) to correctly image the hybridized arrays, and (ii) to correctly analyze the images to extract quantitative data. Existing optical imaging systems typically image one region of an array at a time, which can be a slow process if a number of different regions need to be imaged. In addition, current methods of image analysis typically determine a signal intensity level (i.e. an analog quantity) for each array feature. Intensity level measurements are often subject to a variety of instrumental drift and analysis errors, therefore improved methods for determining whether or not target molecules are bound to a given array feature, and improved methods for transforming that data into quantitative measures of the number of target molecules present in a sample, are of great importance to expanding the use of array technologies in biomedical applications.
SUMMARY OF THE INVENTION
The methods, systems, and platforms of the present disclosure provide means for digital counting of labeled features on arrays, and thereby enable quantitative determination of the number of target molecules present in a sample through the use of stochastic labeling techniques.
In some embodiments, an array reader system comprising an output unit for calculating an absolute number of target molecules in a sample is described, wherein the array reader system is configured to read an array comprising a plurality of labeled and non-labeled features. In some embodiments, the array reader system may further comprise an optical imaging system. In some embodiments, the calculation of absolute number of target molecules in a sample is based on transforming optical image data produced by the optical imaging system into a count of the number of labeled and non-labeled features on an array. In some embodiments, the output unit comprises a digital processor and executable software, wherein the executable software comprises computer code for transforming optical image data into a count of the number of labeled and non-labeled features. In some embodiments, the array comprises a microarray, microscope slide, or microwell plate.
In some embodiments of the disclosed array reader system, the optical imaging system has a magnification of less than 1, equal to 1, or greater than 1. In some embodiments, the optical imaging system comprises a fluorescence imaging system. In some embodiments, the optical imaging system comprises a phosphorescence imaging system. In some embodiments, the optical imaging system comprises an imaging system that operates in a transmitted light, reflected light, or scattered light imaging mode, or combinations thereof. In some embodiments, the optical imaging system comprises one or more image sensors, wherein the one or more image sensors have a resolution of at least 320×240 pixels. In some embodiments, the one or more image sensors are CCD image sensors, while in some embodiments, the one or more image sensors are CMOS image sensors. In some embodiments, the one or more image sensors comprise one or more circuit boards. In some embodiments, the optical imaging system further comprises one or more components selected from the group including, but not limited to, a microscope objective, a camera lens, a finite-conjugate lens, an infinite-conjugate lens, a plano-convex lens, a double convex lens, a plano-concave lens, a double concave lens, an achromatic cemented doublet, or a bandpass filter. In some embodiments, the optical imaging system comprises a fluorescence imaging system that is designed for use with fluorescein, Cy3, Cy5, or phycoerythrin fluorophores. In some embodiments, the optical imaging system further comprises an illumination system including at least one light source, wherein the at least one light source is an LED or LED assembly. In some embodiments, the at least one light source is electronically synchronized with the image sensor, the at least one light source being turned on when the image sensor is acquiring an image and turned off when the image sensor is not acquiring an image.
In some embodiments of the disclosed array reader system, the illumination system is an off-axis illumination system that satisfies the Scheimpflug condition. In some embodiments, the illumination system is an off-axis illumination system does not satisfy the Scheimpflug condition. In some embodiments, the illumination system is an off-axis illumination subsystem comprising a Kohler illumination system. In some embodiments, the illumination system is an off-axis illumination system comprising an Abbe illumination system. In some embodiments, the illumination system is an epi-illumination system comprising a Kohler illumination system. In some embodiments, the illumination system is an epi-illumination system comprising an Abbe illumination system. In some embodiments, the illumination system is a trans-illumination system comprising a Kohler illumination system. In some embodiments, the illumination system is a trans-illumination system comprising an Abbe illumination system.
In some embodiments of the disclosed array reader system, the optical imaging system further comprises a translation stage, wherein the translation stage is a single-axis translation stage, a dual-axis translation stage, or a multi-axis translation stage.
In some embodiments of the disclosed array reader system, the optical imaging system and output unit are combined within a single, stand-alone instrument. In some embodiments, the optical imaging system and output unit are configured as separate instrument modules.
In some embodiments of the disclosed array reader system, the executable software automatically locates features of the array within the acquired image. In some embodiments, the executable software also performs local background correction by (i) centering a predefined analysis window on each array feature within an image, (ii) calculating an intensity value statistic for signal and background pixels according to a predefined pattern of pixels within the feature, and (iii) utilizing the signal and background intensity value statistics to calculate a background corrected signal intensity value for each feature.
In some embodiments of the disclosed array reader system, the executable software performs a k-means clustering analysis of the background corrected signal intensity values for the complete set of array features, thereby determining a dynamic signal intensity threshold for discrimination between labeled and non-labeled features of the array. In some embodiments, the executable software also performs a k-medoids clustering analysis of the background corrected signal intensity values for the complete set of array features, thereby determining a dynamic signal intensity threshold for discrimination between labeled and non-labeled features of the array. In some embodiments, the executable software also performs a mixture model statistical analysis of the background corrected signal intensity values for the complete set of array features, thereby determining a dynamic signal intensity threshold for discrimination between labeled and non-labeled features of the array. In some embodiments, the executable software also performs an empirical analysis based on sorting of background corrected signal intensity values for the complete set of array features, thereby determining a dynamic signal intensity threshold for discrimination between labeled and non-labeled features of the array. In some embodiments, the executable software also performs an empirical analysis based on sorting of pairwise differences in background corrected signal intensity values for the complete set of array features, thereby determining a dynamic signal intensity threshold for discrimination between labeled and non-labeled features of the array. In some embodiments, the executable software module also performs one or more statistical analyses of the background corrected signal intensity values for the complete set of array features, thereby determining a dynamic signal intensity threshold for discrimination between labeled and non-labeled features of the array, and wherein the one or more statistical analyses are selected from the list including, but not limited to, k-means clustering, k-medoids clustering, mixture model statistical analysis, or an empirical analysis.
In some embodiments of the disclosed array reader system, the executable software calculates the absolute number of target molecules in a sample based on the number of labeled and non-labeled features detected and the predictions of the Poisson distribution. In some embodiments, the executable software also calculates a confidence interval for the number of target molecules.
Also disclosed herein is a digital imaging platform comprising: (a) an optical instrument configured to generate an image of one or more regions of an array, wherein the array comprises a plurality of features comprising oligonucleotide probes, and wherein the oligonucleotide probes are complementary to a set of labels; and (b) a digital processor, wherein the digital processor is configured to perform image analysis comprising: (i) transforming background corrected signal intensities for a plurality of features to produce binary output data that determines the number of labeled and non-labeled features in the one or more regions of the array; and (ii) calculating a number of target molecules present in a sample based on the number of labeled and non-labeled features detected within the one or more regions of the array. In some embodiments, the image analysis further comprises automatically locating the features of the array within the image. In some embodiments, the image analysis further comprises correcting a signal intensity for each feature for a local background intensity. In some embodiments, the image analysis further comprises performing one or more statistical analyses of the corrected signal intensities for a plurality of features to define one or more dynamic signal intensity thresholds for the one or more regions of the array, where the statistical analyses are selected from the list including, but not limited to, k-means clustering, k-medoids clustering, mixture model statistical analysis, or an empirical analysis. In some embodiments, the calculation of the number of target molecules present in a sample is based on both the number of labeled and non-labeled features detected within the one or more regions of the array and on the predictions of the Poisson distribution.
Disclosed herein is an imaging platform comprising: (a) an optical instrument configured to generate an image of one or more regions of an array, wherein the array comprises a plurality of features, and wherein the plurality of features comprise a set of oligonucleotide probes, and wherein the oligonucleotide probes are complementary to a set of labels; and (b) a processor configured to perform image analysis, wherein the image analysis comprises: (i) reading the image generated by the optical instrument; (ii) locating the features of the array within the image; (iii) measuring a signal intensity for each feature; (iv) measuring a local background intensity for each feature; (v) calculating a local background corrected signal intensity for each feature using the signal intensity and local background intensities; (vi) analyzing the local background corrected signal intensities for the complete set of features to determine a dynamic signal intensity threshold for discriminating between labeled and non-labeled features; and (vii) calculating a number of target molecules present in a sample based on the number of labeled and non-labeled features detected and the predictions of the Poisson distribution. In some embodiments, the image generated by the optical instrument is a fluorescence image. In some embodiments, the image generated by the optical instrument is a phosphorescence image. In some embodiments, the image generated by the optical instrument is a transmitted light, reflected light, or scattered light image. In some embodiments, the image analysis further comprises reading an image that has been previously acquired and stored in a memory device. In some embodiments, locating the features of the array within the image comprises identifying predefined fiducial features on the array. In some embodiments, the calculation of a local background corrected signal intensity is performed by (i) centering a predefined analysis window on each feature within the image, (ii) calculating an intensity value statistic for signal and background pixels according to a predefined pattern of pixels within the feature, and (iii) utilizing the signal and background intensity value statistics to calculate a local background corrected signal intensity for each feature. In some embodiments, the intensity value statistic used for calculating a local background corrected signal intensity for each feature is selected from the list including, but not limited to, the mean, the median, or the ratio of signal to background intensities. In some embodiments, the analyzing of local background corrected signal intensities for the complete set of features to determine a dynamic signal intensity threshold comprises performing one or more statistical analyses selected from the list including, but not limited to, k-means clustering, k-medoids clustering, mixture model statistical analysis, or an empirical analysis. In some embodiments, the analyzing of local background corrected signal intensities for the complete set of features to determine a dynamic signal intensity threshold comprises fitting a model function to the intensity data by varying model parameters. In some embodiments, the analyzing of local background corrected signal intensities for the complete set of features to determine a dynamic signal intensity threshold comprises maximizing a quality metric relating to a statistical difference between intensities above the threshold and below the threshold.
Also disclosed herein is a non-transitory computer readable medium storing a program that calculates a number of labeled features on an array, wherein the array comprises a plurality of feature sets, and wherein individual features of a feature set comprise a set of oligonucleotide probes that are capable of hybridizing to a set of labels, the non-transitory computer readable medium comprising: (a) computer code that locates individual features of the array within a digital image of the array; (b) computer code that performs a local background correction of a signal intensity for each feature; (c) computer code that analyzes the corrected signal intensity data for the complete set of features and determines a corrected signal intensity threshold; and (d) computer code that transforms the corrected signal intensity for each feature into binary output data, thereby providing a count of the number of labeled features on the array. In some embodiments, the computer code for locating individual features of the array within the digital image comprises identifying predefined fiducial features on the array. In some embodiments, the computer code for performing a local background correction of signal intensity for each feature comprises a calculation utilizing a statistic for signal and background intensities selected from the list including, but not limited to, the mean, the median, or the ratio of signal to background intensities. In some embodiments, the computer code for analyzing corrected signal intensities for the complete set of features to determine a corrected signal intensity threshold comprises performing one or more statistical analyses selected from the list including, but not limited to, k-means clustering, k-medoids clustering, mixture model statistical analysis, or an empirical analysis.
Also disclosed herein is a computer implemented method for performing local background correction of array signal intensity data, the method comprising: (a) centering a predefined data analysis window on a feature within a digital image of the array; (b) calculating an intensity value statistic for signal and background pixels according to a predefined pattern of pixels within or around the array feature; and (c) utilizing the signal and background intensity value statistics to calculate a background corrected signal intensity for the array feature. In some embodiments, the computer implemented method further comprises automatically locating the array feature using a predefined set of fiducial features on the array. In some embodiments, the intensity value statistic used for calculation of a background corrected signal intensity is selected from the list including, but not limited to, the mean, the median, or the ratio of signal to background intensities.
Disclosed herein is a computer implemented method for determining a dynamic image intensity threshold for use in discriminating between labeled and non-labeled features on an array comprising a plurality of labeled and non-labeled features, the computer implemented method comprising: (a) measuring image intensity data for each feature of the array; (b) performing a local background correction on the image intensity data for each feature on the array; and (c) performing one or more statistical analyses of the background corrected image intensity data for the complete set of array features, thereby determining a dynamic image intensity threshold for discrimination between labeled and non-labeled features of the array, and wherein the one or more statistical analyses are selected from the list including, but not limited to, k-means clustering, k-medoids clustering, mixture model statistical analysis, or an empirical analysis.
Also disclosed is a mechanism comprising: (a) a closure; (b) a housing which magnetically holds the closure in a first position; and (c) a translation stage which magnetically holds the closure in a second position. In some embodiments, the mechanism further comprising a gasket positioned between the closure and the housing. In some embodiments, the gasket is attached to the closure. In some embodiments, the gasket is attached to the housing. In some embodiments, the closure and housing are substantially opaque, and the gasket creates a substantially light-tight seal between the closure and the housing in the first position. In some embodiments, one or more magnets are positioned to hold the closure onto the housing in the first position. In some embodiments, one or more magnets are positioned to hold the closure onto a first surface of the translation stage in the second position. In some embodiments, two or more pairs of mating locating features to align the closure with the translation stage in the second position. In some embodiments, two or more pairs of mating locating features to align the closure with the housing in the first position. In some embodiments, the pairs of mating locating features comprise conical pins and conical holes. In some embodiments, the housing comprises an optical instrument. In some embodiments, the translation stage includes a sample holder. In some embodiments, the sample holder is designed to hold a microscope slide, a microarray, or a microwell plate. In some embodiments, the closure is not hinged. In some embodiments, the closure is not attached to either the housing or the translation stage through the use of fasteners such as screws or clips. In some embodiments, the closure is not attached to either the housing or the translation stage through the use of an adhesive.



BRIEF DESCRIPTION OF THE DRAWINGS
The novel features of the invention are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present invention will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings of which:
FIGS. 1A-1G show one example of an optical system, and components thereof. FIG. 1A depicts an isometric projection of the exemplary optical system. FIG. 1B depicts a top view of the optical system. FIG. 1C depicts a dimetric view of the optical system. FIG. 1D depicts a front view of the optical system. FIG. 1E depicts a side view of the exemplary optical system comprising a single axis stage, an imaging system, and an illumination system. FIG. 1F depicts a back view of the optical system. FIG. 1G depicts components that control the operation of the optical system.
FIG. 2 shows an exemplary layout of lenses in an imaging system.
FIG. 3 shows an exemplary layout of lenses in an illumination system.
FIG. 4A shows an array image acquired from the optical instrument. FIG. 4B shows a histogram of intensities for individual features.
FIG. 5 shows a feature intensity distribution observed for hybridization of array probes with labeled target molecules in atitration experiment.
FIG. 6A shows a noisy array image. FIG. 6B shows the intensity distribution before background adjustment. FIG. 6C shows the intensity distribution after background adjustment.
FIGS. 7A-7D show external views of instrument designed for digital counting of features on arrays. FIG. 7A is an axonometric view of the instrument as viewed from the upper right. FIG. 7B is an axonometric view of the instrument as viewed from the right-front. FIG. 7C is a front view of the instrument. FIG. 7D is an axonometric view of the instrument as viewed from the upper left.
FIG. 8 shows an internal view (front view; 3D CAD model) of an instrument designed for digital counting of features on arrays.
FIG. 9 depicts an internal view (rear view; 3D CAD model) of an instrument designed for digital counting of features on arrays.
FIG. 10 shows a photograph of a system with the sample loading stage in the extended (loading) position, having pulled the door away from the front panel. A Pixel 16 array assembly is shown in the loading tray.
FIG. 11A shows an exploded view of a door assembly that utilizes a magnetic mechanism for positioning a door on a sample compartment stage. FIG. 11B shows another exploded view of the door assembly that illustrates conical locator features for ensuring proper alignment of the door with the stage.
FIG. 12 depicts an exploded view of an upper stage assembly with magnets which mate with a corresponding pair of magnets on the door.
FIG. 13 shows an exploded view of a front panel assembly with magnets which mate with a corresponding pair of magnets on the door.
FIG. 14 shows the viewing reference orientation for array production and analysis in one embodiment of an array, showing the 16 array locations on a glass substrate. Nominal dimensions are shown (in millimeters).
FIG. 15 shows the layout of features on one embodiment of an array. Nominal dimensions are shown (in millimeters).
FIG. 16 shows the layout of an array designed for digital counting of target molecules in a sample, including the positions of positive controls (fiducials), negative controls, and index spots.
FIG. 17A shows an example of an array image after transformation to the reference orientation. FIG. 17B shows the image size (in pixels) and a schematic of feature positions for the two-array image.
FIGS. 18A-B depict software workflows for performing an experiment on an instrument designed for digital counting of features on arrays. FIG. 18A: workflow for a single-axis system with manual sample loading. FIG. 18B: workflow for a dual-axis system with automatic sample tray loading.
FIG. 19 depicts an analysis window comprising a 12×12 pixel area associated with each feature in the array.
FIG. 20 depicts a map of the pixel designations within the analysis window for each feature in the array.
FIG. 21 depicts a scatter plot (upper) of intensity data obtained from an image of an array that illustrates the different categories of features identified by the analysis software, and a histogram (lower) of the feature intensity data. Dashed lines indicate examples of intensity thresholds determined by the software that are used to discriminate between labeled (“on”) and non-labeled (“off”) features.
FIG. 22 depicts a scatter plot (upper) and histogram (middle) of array feature intensity data that illustrate the use of an intensity threshold (dashed lines) that discriminate between labeled (“on”) and non-labeled (“off”) features of an array. In one embodiment of the presently described analysis methods, the threshold is determined from the maximum slope of a plot of sorted intensity data (lower).
FIG. 23 depicts the results of fitting a 3-component distribution model used to determine an intensity threshold in one embodiment to a 128-bin feature intensity histogram.
FIG. 24A illustrates deviance calculations for fitting one normal distribution to histograms of array feature intensity data. FIG. 24B illustrates the deviance calculations for fitting two normal distributions to histograms of array feature intensity data. In some embodiments, deviance measurement may be used as a quality metric.
FIG. 25 depicts the uncertainties calculated for various methods of combining output data from replicate experiments.
FIG. 26 shows dilution series data for using digital counting of labeled features on an array to measure the number of target RNA molecules in a sample.
FIG. 27 shows a screenshot of the output data provided by the system software for a dilution series experiment. For each array used in the dilution series experiment, the software displays a histogram of feature intensity data with a blue line indicating the value of the threshold used for counting, overlaid on a digital representation of the array.



DETAILED DESCRIPTION OF THE INVENTION
Array technologies have been widely used in biomedical studies for the detection of biomolecules and profiling of gene expression levels, etc. Arrays are typically comprised of immobilized probes which can bind to or hybridize with target molecules in a sample. Detection of binding or hybridization events is often achieved through the use of optical labels (e.g. fluorophores) and scanning or imaging techniques (e.g. fluorescence scanning or imaging). A feature on an array is a small region of immobilized probes that are specific for a given target molecule, e.g. probes that hybridize to specific DNA or RNA sequences. Identifying the pattern of labeled features on a hybridized array thus provides information about the presence of specific molecules, e.g. DNA or RNA molecules in the sample, which in turn can provide valuable data in biomedical studies. Two important engineering requirements for providing high quality, quantitative data for biomedical investigations are (i) to correctly image the hybridized arrays, and (ii) to correctly analyze the images to extract quantitative data. Existing optical imaging systems typically image one region of an array at a time, which can be a slow process if a number of different regions need to be imaged. In addition, current methods of image analysis typically determine an analog signal intensity level (i.e. a signal that can have any value between some minimum and maximum values that are determined by various instrumental and experimental parameters) for each array feature. Analog intensity level measurements are often subject to a variety of instrumental drift and analysis errors, therefore improved methods for determining whether or not target molecules are bound to a given array feature, and improved methods for transforming that data into quantitative measures of the number of target molecules present in a sample, are of great importance to expanding the use of array technologies in biomedical applications.
The advantages of the methods, systems, and platforms disclosed herein include: (i) simultaneous imaging of multiple regions of an array for higher throughput image acquisition, and (ii) improved methods for reduction of image data to a digital determination of the presence or absence of bound target molecules (or target molecule labels) for each feature of an array, thereby providing for improved quantitation in some types of array experiments, for example, those utilizing a set of stochastic labels for quantifying the number of target molecules present in a sample. The use of stochastic labeling techniques is described in U.S. Pat. No. 8,835,358 and PCT application US2011/065291, which are incorporated in their entirety herein by reference. In addition to providing a means for more quantitative detection of target molecules, the use of stochastic labeling techniques allows for mitigation of amplification bias in assays involving nucleic acid amplification.
Accordingly, disclosed herein are methods, devices, systems, and platforms for digital counting of labeled features on arrays comprising: (i) optical instruments configured to form images of one or more regions of an array, (ii) arrays comprising a plurality of features further comprising a plurality of probes, and wherein one or more regions of an array may comprise one or more sub-arrays, and wherein the arrays or sub-arrays are designed for use with sets of stochastic labels, and (iii) computer implemented methods for receiving input image data; locating array features within array images; correcting the signal intensity values associated with each feature for local background intensity values; determining dynamic signal intensity thresholds for the one or more array regions by performing statistical analyses of the corrected signal intensity data for a plurality of features; counting the number of labeled and non-labeled features on the one or more regions of the array by comparing corrected signal intensity data for the features to signal intensity thresholds; and calculating the number of target molecules in a sample, for one or more target molecule species, from the number of labeled and non-labeled features detected on the one or more regions of the array.
In some embodiments, systems are described which comprise: (i) an optical instrument (or reader) configured to form images of one or more regions of an array, (ii) a digital processor configured to perform executable instructions and store data in memory devices, and (iii) computer code for performing image analysis in order to transform image data into a digital count of the number of labeled and non-labeled features on the one or more regions of the array. In some embodiments, the computer code further comprises performing a calculation of the number of target molecules in a sample, for one or more target molecule species, from the number of labeled and non-labeled features detected on the one or more regions of the array.
In some embodiments, platforms are described which comprise: (i) arrays designed for use in stochastic labeling experiments, wherein the arrays comprise a plurality of features further comprising a plurality of probes, and wherein one or more regions of an array may comprise one or more sub-arrays, and wherein the arrays or sub-arrays are designed for use with sets of stochastic labels, (ii) an optical instrument (or reader) configured to form images of one or more regions of an array, (iii) a digital processor configured to perform executable instructions and store data in memory devices, and (iv) computer code for performing image analysis in order to transform image data into a digital count of the number of labeled and non-labeled features on the one or more regions of the array. In some embodiments, the computer code further comprises performing a calculation of the number of target molecules in a sample, for one or more target molecule species, from the number of labeled and non-labeled features detected on the one or more regions of the array.
In some embodiments, software applications (or computer code products) are described that determine the number of labeled features on an array, wherein the software application includes code for performing one or more of the following computer implemented methods: (i) receiving input image data, (ii) locating array features within array images, (iii) correcting the signal intensity values associated with each feature for local background intensity values, (iv) determining dynamic signal intensity thresholds for the one or more array regions by performing statistical analyses of the corrected signal intensity data for a plurality of features, (v) counting the number of labeled and non-labeled features on the one or more regions of the array by comparing corrected signal intensity data for the features to signal intensity thresholds, and (vi) calculating the number of target molecules in a sample, for one or more target molecule species, from the number of labeled and non-labeled features detected on the one or more regions of the array.
In some embodiments, computer implemented methods are described for performing local background correction of array signal intensity data, the methods comprising: (i) centering a predefined data analysis window on each array feature within a digital image of the array, (ii) calculating mean or median intensity values for signal and background pixels according to a predefined pattern of pixels within or around each array feature, and (iii) subtracting the mean or median background intensity from the mean or median signal intensity to determine a background corrected signal intensity value for each array feature.
In some embodiments, computer implemented methods are described for determining dynamic image intensity thresholds from the corrected image intensity data for a plurality of features on an array, the methods comprising: (i) collecting image intensity data for each feature of the array, (ii) optionally performing a local background correction on the image intensity data for each feature on the array; and (iii) performing one or more statistical analyses of the background corrected image intensity data for the complete set of array features, thereby determining a dynamic image intensity threshold for discrimination between labeled and non-labeled features of the array. In some embodiments, the one or more statistical analyses are selected from the list including, but not limited to, k-means clustering, k-medoids clustering, mixture model statistical analysis, or empirical analyses based on sorting of image intensity values or pairwise differences in image intensity values. As used herein, the term “dynamic intensity threshold” refers to a parameter that is determined based on an analysis of data derived from the experiment in progress. The use of a dynamic image intensity threshold for discrimination between labeled and non-labeled features of an array helps to minimize or eliminate errors in data processing that may arise from instrumental drift or experimental procedure.
DEFINITIONS
Unless otherwise defined, all technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art in the field to which this disclosure belongs. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise. Any reference to “or” herein is intended to encompass “and/or” unless otherwise stated.
As used herein, the terms “system” and “platform” are used interchangeably. Similarly, the terms “image sensor”, “imaging sensor”, “sensor chip”, and “camera” are used interchangeably to describe two dimensional photosensors used for imaging purposes, and the use of the terms “image intensity” and “signal intensity” are also used interchangeably in describing data analysis methods. Finally, unless otherwise stated, the terms “software”, “software application”, “software module”, “computer program”, and “computer code” are also used interchangeably.
Stochastic Labeling Methods
The use of stochastic labeling techniques is described in U.S. Pat. No. 8,835,358 and PCT application US2011/065291, which are incorporated in their entirety herein by reference.
Briefly, high-sensitivity single molecule digital counting may be achieved through the stochastic labeling of a collection of identical target molecules. Each copy of a target molecule is randomly labeled using a large, non-depleting reservoir of unique labels. The uniqueness of each labeled target molecule is determined by the statistics of random choice, and depends on the number of copies of identical target molecules in the collection compared to the diversity of labels. The size of the resulting set of labeled target molecules is determined by the stochastic nature of the labeling process, and analysis of the number of labels detected then allows calculation of the number of target molecules present in the original collection or sample. When the ratio of the number of copies of a target molecule present to the number of unique labels is low, the labeled target molecules are highly unique (i.e. there is a very low probability that more than one target molecule will have been labeled with a given label), and the digital counting efficiency is high. This stochastic metholodology transforms the problem of counting molecules from one of locating and identifying identical molecules to a series of yes/no digital questions regarding detection of a set of predefined labels. In some embodiments, the labeled products are detected by means of DNA sequencing. In other embodiments, the labeled products for one or more target molecules of choice are detected with high specificity using the array readout systems described herein.
Arrays and Features
Disclosed herein are arrays designed for use in stochastic counting of one or more target molecules in a sample. Arrays provide a means of detecting the presence of labeled target molecules, wherein the labels comprise a large and diverse set of unique labels.
In many embodiments, arrays comprise a plurality of features (or spots) on the surface of a substrate, wherein each feature further comprises a plurality of attached probes. In some embodiments, the array may comprise one or more regions, each of which may comprise a plurality of features or sub-arrays. For example, an array may comprise 2, 3, 4, 5, 6, 7, 8, 9, 10 or more regions, or alternatively, an array may comprise 15, 20, 25, 30, 35, 40, 45, 50 or more regions. In some embodiments, an array may comprise 60, 70, 80, 90, 100 or more regions. In other embodiments, an array may comprise hundreds, thousands, or tens of thousands of regions.
Non-limiting examples of arrays include microtiter plates, microwell plates, 16-well microscope slides, spotted microarrays, or microarrays fabricated by in situ solid-phase synthesis. A region of an array may comprise one well of a 16-well microscope slide, one well of a glass-bottomed 96-well plate, or one well of a glass-bottomed 384-well plate. Alternatively, a region of an array may comprise more than one well, for example, in some embodiments, a region may comprise 2 adjacent wells, 4 adjacent wells; or a larger number of wells positioned in close proximity to each other. In some embodiments, the arrays may comprise high-density oligonucleotide arrays with more than 1,000 features per square millimeter, and a region on the array may comprise a selected area of the array substrate surface, for example, an area of approximately 1 mm×1 mm.
As indicated previously, in many embodiments, the set of probes attached to a set of features of an array are selected for detection of a specific set of unique labels designed for use in stochastic labeling studies. The attachment of the probes to the array substrate may be covalent or non-covalent, and permanent or temporary. A probe may be a sequence of monomers including, but not limited to, for example, deoxy-ribonucleotides, ribonucleotides, amino acids, or synthetic monomers, or they may be a sequence of oligomers, including, but not limited to, for example, oligonucleotides (e.g. DNA or RNA sequences) or peptide sequences. In some cases, a probe may be a macromolecule, including but not limited to, for example, antibodies or antibody fragments. Each feature on an array corresponds to a small area of the array substrate comprising immobilized probes having the same molecular sequence that bind to or hybridize with the same target molecule. Two or more features on the array may be identical, similar, or different. In many embodiments, arrays will include one or more fiducial marks used for alignment or orientation purposes, as well as positive and negative control features in addition to feature sets used for detection of a stochastic label set. Positive control features may comprise probes that bind to or hybridize with molecules known to be always present in a sample, or probes that bind to or hybridize with molecules spiked into a sample in a controlled fashion. Negative control features may comprise probes that are specific for molecules that are known to be absent from a sample, or they may comprise features having no probes attached to the substrate surface at all.
In many embodiments, the array substrate, also called a support, may be fabricated from a number of materials. The materials may be solid. The materials may be semi-solid. Examples of materials that may be used to fabricate array substrates include, but are not limited to, glass, fused silica, silicon, polymer, or paper.
In some embodiments, the present disclosure also describes arrays for use in stochastic labeling studies. In particular, arrays are described wherein the arrays comprise a plurality of features having immobilized probes thereon that are complementary to a set of labels designed for use in stochastic labeling experiments, and wherein there is at least one feature on the array for every label in the label set. Some embodiments include an array comprising: (a) a plurality of features, optionally organized into a plurality of sub-arrays, wherein the plurality of features comprise: (i) one or more fiducial features comprising oligonucleotide probes of a defined fiducial sequence; (ii) one or more positive control features comprising oligonucleotide probes of one or more defined positive control sequences; (iii) one or more negative control features having no oligonucleotide probes; and (iv) a plurality of label set features comprising oligonucleotide probes, wherein each individual feature comprises a unique sequence selected from a set of label sequences designed for stochastic labeling of one or more target molecules. In some embodiments, the arrays described in the present disclosure comprise oligonucleotide probe sequences comprising 25-mers, wherein the 5′ terminus may optionally be labeled with a 6 carbon atom amino-modifier. In some embodiments, the arrays described in the present disclosure further comprise oligonucleotide probes comprising the set of 960 unique oligonucleotide sequences listed in Table 1. In some embodiments, the arrays described in the present disclosure comprise a set of olignucleotide probes that are 70% homologous, 80% homologous, 85% homologous, 90% homologous, or 95% homologous with the set of sequences listed in Table 1. In some embodiments, the array described in the present disclosure comprise a set of oligonucleotide probes that includes 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, or 90% or more of the sequences listed in Table 1.
Hybridization and Detection
In many embodiments of the disclosed methods, systems, and platforms, samples may be processed prior to placing them in contact with the immobilized probes on arrays. For example, target molecules in the samples may be labeled with fluorescent dye molecules and/or stochastic labels during the sample preparation step. Prior to hybridization with oligonucleotide probes, for example, target DNA or RNA molecules may be covalently linked to fluorescent dye molecules including, but not limited to, fluorescein, Cy3, or Cy5. Alternatively, target molecules may be labeled after binding or hybridizing to probes on the array. For example, target molecules may be covalently linked to biotin prior to binding or hybridization with probes on the array. Following the binding or hybridization step, the immobilized target molecules may then be labeled with streptavidin conjugated to optical tags including, but not limited to, phycoerythrin, quantum dot nanoparticles, gold nanoparticles, or blue latex beads. There are many methods for labeling target molecules, either before or after binding or hybridization to the array, and many possible choices for suitable optical labels or tags.
Once a sample has been contacted with an array, the array (or one or more regions of the array) may comprise one or more labeled features. Each region of an array that has been contacted with a sample comprising labeled target molecules (where the target molecules are labeled either before or after contact with the array) may, for example, comprise zero, one, two, or more labeled features. Alternatively, a region of an array that has been contacted with a sample may comprise 2, 3, 4, 5, 6, 7, 8, 9, 10 or more labeled features. In some embodiments, a region of an array that has been contacted with a sample may comprise 15, 20, 25, 30, 35, 40, 45, 50, or more labeled features. In high-density arrays, a region of an array that has been contacted with a sample may comprise more than 100 labeled features, more than 1,000 labeled features, more than 10,000 labeled features, more 100,000 labeled features, or more than 1,000,000 labeled features.
Optical Instruments
The methods, systems, and platforms described herein may comprise an optical instrument used for finite-conjugate digital imaging of one or more regions of an array, wherein the instrument typically includes an illumination system, an imaging system, and a translation stage. In some embodiments, the instrument operates as a “macroscope” having a magnification of less than one. In other embodiments, the instrument operates as a “microscope” having a magnification of greater than one. In still other embodiments, the instrument operates as a “contact imager” having a magnification equal to one. The choice of magnification will typically depend on the field of view required to image the region of interest, and on the size of the image sensor.
By way of non-limiting example, if a region of an array comprises a single well of a 16-well microscope slide, or a single well of a glass-bottomed 96-well plate, the dimensions of the region to be imaged may be approximately 7 mm×7 mm, and the pitch (center-to-center distance between two adjacent regions of the array may be approximately 9 mm. In some embodiments, the optical instrument may be used to take an image of one well at a time, or an image of 2 adjacent wells simultaneously, or an image of 4 (2×2) adjacent wells simultaneously, and the required field of view, or region to be imaged, may be adjusted accordingly. Similarly, the optical instrument may form an image of 6 (3×2 or 2×3), 8 (4×2 or 2×4), 9 (3×3), 10 (5×2 or 5×2), or 12 (6×2, 4×3, 3×4, or 2×6) adjacent wells simultaneously.
By way of another non-limiting example, if a region of an array is a single well of a glass-bottomed 384-well plate, the dimensions of the region to be imaged may be approximately 3 mm×3 mm, and the pitch between two adjacent regions of the array may be approximately 4.5 mm. Again, in some embodiments, the optical instrument may be used to take an image of one well at a time, or an image of 2 adjacent wells simultaneously, or an image of 4 (2×2), 6 (3×2 or 2×3), 8 (4×2 or 2×4), 12 (4×3 or 3×4), or 16 (4×4) adjacent wells simultaneously.
In another non-limiting example, the optical instrument may be used to image high-density oligonucleotide arrays, for example arrays having more than 1,000 features per square millimeter, and a region on the array may be approximately 1 mm×1 mm in area, for example.
Imaging System
One main component of the optical instrument is an imaging system. The imaging system may include one or more lenses in addition to a CCD or CMOS camera. Typically the CCD or CMOS camera will have a resolution between a few hundred thousand and a few million pixels. A high resolution camera may have tens of millions of pixels, or more.
The imaging system may be configured to magnify the image of the array. The required magnification of the imaging system can be determined by the required field of view and by the size of the CCD or CMOS sensor. By way of a non-limiting example, if the optical instrument is used to take an image of 2 adjacent wells of a 16-well microscope slide simultaneously, the required field of view is approximately 16 mm×8 mm. If the light-sensitive area of the CCD or CMOS sensor is about 4.8 mm×3.6 mm, the instrument is a macroscope and a magnification of about 0.3 is required. In this case, only data from the central 4.8 mm×2.4 mm of the sensor would be used.
By way of non-limiting example, an appropriate imaging system with a magnification of 0.3 may be constructed using an achromatic cemented doublet lens with a focal length of 85 mm and an infinite-conjugate camera lens with a focal length of 25 mm. If a spectrally selective emission filter is used (for example, a single-band interference filter, multi-band interference filter, longpass interference filter, or longpass colored glass filter), and this filter is typically located between the achromatic cemented doublet lens and the camera lens. Additional configurations of an imaging system with a magnification of 0.3 are possible. For example, the achromatic cemented doublet lens can be omitted, and a finite-conjugate camera lens can be used instead of an infinite-conjugate camera lens. In this case, the spectrally selective emission filter is preferably located on the long-conjugate side of the camera lens.
A sensor with a light-sensitive area of 4.8 mm×3.6 mm is known as a 1⁄3-inch format sensor. If a sensor of different size is used, the required magnification will be different. By way of a non-limiting example, if the required field of view is 16 mm×8 mm and a sensor having a light-sensitive area of 6.4 mm×4.8 mm (known as a 1⁄2-inch format sensor) is used, then the required magnification is 0.4. An appropriate imaging system with a magnification of 0.4 can be constructed using, for example, an achromatic cemented doublet lens with a focal length of 85 mm and an infinite-conjugate camera lens with a focal length of 35 mm.
As another non-limiting example, if the dimensions of a region are about 0.66 mm×0.66 mm and a sensor with a light-sensitive area of 8.8 mm×6.6 mm (known as a 2⁄3-inch format sensor) is used, then the instrument is a microscope and the required magnification is about 10. In this case, only data from the central 6.6 mm×6.6 mm of the sensor will be used. An appropriate imaging system with a magnification of 10 can be constructed using, for example, an infinite-conjugate microscope objective with a focal length of 20 mm and a microscope tube lens with a focal length of 200 mm, with a spectrally selective emission filter typically located between the microscope objective and the tube lens. Alternatively a finite-conjugate 10× microscope objective can be used and the microscope tube lens can be omitted. In this case the spectrally selective emission filter can be located on the long-conjugate side of the microscope objective.
An imaging system of any required magnification can be constructed using a combination of off-the-shelf and custom optical elements that does not necessarily include either a camera lens or a microscope objective. The optical elements may have various combinations of spherical, flat, aspheric, or diffractive surfaces.
Illumination System
Another main component of the optical instrument is an illumination system. The purpose of the illumination system is to illuminate the array within the field of view of the CCD or CMOS camera. To reduce sensitivity to edge effects and to misalignment, it may be desirable for the illuminated area to be slightly larger than the camera's field of view. By way of a non-limiting example, if the field of view is about 16 mm×8 mm, a reasonable illuminated area may be about 18 mm×10 mm. The types of illumination may be Abbe, Kohler, or neither Abbe nor Kohler illumination. Abbe illumination and Kohler illumination are well known and are described in, for example, Chapter 14 of Optical System Design, Second Edition by Robert E. Fischer et al., SPIE Press, McGraw-Hill, N.Y., 2008.
In some embodiments, the illumination system may be used for off-axis illumination. In other embodiments, the illumination system may be used for trans-illumination or epi-illumination. If the illumination system is used for off-axis illumination or trans-illumination, then the illumination system and the imaging system are separate from each other, with no shared optical components. If the illumination system is used for epi-illumination, then the illumination system and the imaging system may share a beamsplitter and possibly one or more lenses. The beamsplitter may be a plate beamsplitter or a cube beamsplitter. If the optical instrument is used for fluorescence imaging, the beamsplitter is typically a single-edge or multi-edge longpass dichroic beamsplitter.
Often the illumination system may contain a square or rectangular aperture so that the illuminated area has the same shape as the region that is imaged by the CCD or CMOS camera. In embodiments where off-axis illumination is used, the aperture may be trapezoidal in shape instead of square or rectangular. An off-axis illumination system may or may not satisfy the Scheimpflug condition. The Scheimpflug condition is described in, for example, Modern Optical Engineering, Second Edition by Warren J. Smith, McGraw-Hill, N.Y., 1990.
In some embodiments, the illumination system may contain one or more of the following: spherical lenses, aspheric lenses, a solid homogenizing rod with a rectangular or trapezoidal cross section, a hollow homogenizing light tunnel with a rectangular or trapezoidal cross section, a microlens array or a pair of microlens arrays, a stationary or rotating diffuser, a compound parabolic concentrator, a non-imaging optical element other than a compound parabolic concentrator (e.g., a free-form catadioptric element), an optical fiber, a fiber bundle, or a liquid light guide.
The illumination system may contain one or more light sources, selected from the group including, but not limited to, one or more LEDs, one or more lasers, a xenon arc lamp, a metal halide lamp, or an incandescent lamp, or a combination thereof. The illumination system may also contain a spectrally selective excitation filter selected from the list including, but not limited to, a single-band interference filter, a multi-band interference filter, or a shortpass interference filter. If the illumination system contains two or more light sources, they may be the same (by way of non-limiting example, two or more LEDs with peak emission wavelengths of about 525 nm for excitation of Cy3 dye, mounted as close together as possible on a circuit board) or different (by way of non-limiting example, an LED with a peak excitation wavelength of about 525 nm for excitation of Cy3 dye, and an LED with a peak excitation wavelength of about 625 nm for excitation of Cy5 dye, mounted as close together as possible on a circuit board). Two-color or multicolor LED assemblies are available from, for example, LED Engin, Inc. (San Jose, Calif.) and Innovations in Optics, Inc. (Woburn, Mass.).
In some embodiments, a light source in the illumination system may be controlled electronically. By way of a non-limiting example, a light source may be synchronized with the CCD or CMOS camera so that the light source turns on when the CCD or CMOS camera begins an exposure and turns off when the camera finishes an exposure. If the illumination system contains two or more light sources, they may optionally be controlled together or independently of each other.
In some embodiments, a light source may be left on continuously. In this case, the illumination system may contain an electronically controlled shutter, and the shutter may be synchronized with the CCD or CMOS camera so that the shutter opens when the CCD or CMOS camera begins an exposure and closes when the camera finishes an exposure.
In some embodiments, the optical instrument may contain a single illumination system. In other embodiments, the instrument may contain two or more illumination systems that are identical. In yet other embodiments, the instrument may contain two or more illumination systems that are different. By way of non-limiting examples, an optical instrument for detecting fluorescence from Cy3 and Cy5 may contain one illumination system for Cy3 excitation and another illumination system for Cy5 excitation, or it may contain a single illumination system that is used for both Cy3 and Cy5 excitation.
Translation Stage
Yet another main component of the optical instrument may be one or more translation stages. One purpose of the translation stage may be to move sample holders in and out of the field view of the imaging system. Another purpose of the translation stage system may be to move the imaging system, components of the imaging system, the illumination system, or components of the illumination system relative to the sample or relative to one another, for obtaining the best possible image.
In many embodiments of the presently disclosed systems, the translation stage may further comprise a sample holder. By way of non-limiting examples, if the optical instrument is used to take images of 16-well microscope slides, the translation stage contains a slide holder. If the optical instrument is used to take images of 96-well plates or 384-well plates, and it contains a plate holder. The slide holder, plate holder, or other array support holder may be mounted on the translation stage system in any of a variety of ways known to those skilled in the art.
The translation stage may have one or more axes of motion. By way of a non-limiting example, if the support is a 16-well microscope slide and the instrument takes images of 2 adjacent wells simultaneously, a single axis of motion may be sufficient. By way of another non-limiting example, if the support is a 96-well plate and the instrument takes images of 2 adjacent wells simultaneously, then at least 2 axes of motion would be required. Additional axes of motion for adjustment of focus and tilt may also be added. If the instrument can take an image of all of the regions on the support in a single exposure, then the translation stage may be omitted in some embodiments of the optical instrument.
Housing
The systems and devices described herein can include features for insuring that the sensors of the device detect appropriate signal. For example the systems and devices can include light excluding features. The light excluding features generally reduce unintended signal from reaching light sensitive sensors. In many embodiments, one or more of the imaging system, illumination system, translation stage, and other components of the instrument are surrounded by a housing. The housing can be opaque. The housing can, in some instances, act as a faraday cage. In some instances a single housing is sufficient to exclude light from systems. The single housing can also provide external protection of the system. Alternatively, multiple housings may individually contain one or more components of the instrument. In some instances the housings are nested housings. In various embodiments, the housing can be gas and/or liquid tight.
The housing may have an access point which can exclude light from the interior of the housing. The access point may comprise materials that absorb light in the spectrum relevant to the sensors within the housing, e.g. vantablack in the visible spectrum. The access point may comprise a closure device. The closure device may be opaque. The closure device may be, e.g., a door. The closure device may be substantially light-tight in a closed position. The closure may be light-tight in a closed position.
The closure device can be opened, e.g., for insertion and removal of a 16-well slide, 96-well plate, 384-well plate, or other array support. A sensor (for example, a photointerrupter) may be used to determine whether the closure device is open or closed. The instrument's software or electronic hardware may prevent the light source in the illumination system from turning on when the closure device is open, may prevent power from being applied to the image sensor, and/or may prevent the translation stage from moving when the closure device is open.
In some embodiments, the housing may further comprise a mechanism for automated opening and closing of the closure device, as illustrated in FIGS. 10-13. The closure device can provide access to the interior of the housing. The closure device can provide access for the array to be loaded in and out of the instrument. This operation can be performed automatically. In some instances, the closure device can exclude ambient light during imaging, while opening reliably to permit loading.
In some instances the closure device does not comprise pivoting parts. In some embodiments of the disclosed systems and platforms, the closure device is held by magnets to the housing. Magnets can hold the closure device to the housing in a closed position. Magnets can hold the closure device to a loading device, e.g. a tray, in an open position. During a transition from an open to closed position the closure device can transition from being primarily magnetically attached to a loading device to being primarily magnetically attached to the housing. During a transition from a closed to open position the closure device can transition from being primarily magnetically attached to the housing to being primarily magnetically attached to the loading device. In some instances the transition between the open and closed state is magnetically unstable, such instability causing the closure device to move from the transition state to either the more stable open or closed position.
The closure device can comprise a self-locating function provided by conical features on the door. The thicknesses of the parts which support the magnets on each side of a mating pair, and the depth of retaining pockets within those parts, defines the spacing between magnets in each mating pair, and thus the holding forces. The design geometry is matched to the power of the motors to provide enough retaining force, without requiring high motor torque. The system is further designed such that the motor current and speed (and hence torque) can be controlled to improve the performance, and avoid creating a safety hazard. Two of the four magnet pairs are used to temporarily hold the door to the front of the sample tray, when the tray moves outward for loading an array assembly, as depicted in FIG. 10. The other two magnet pairs are used to hold the door closed against the front panel, after the tray has moved inwards (and separated the other two magnet pairs in the process). The respective allocation of magnets is shown in FIG. 11A. The mating magnets on the front of the stage are shown in FIG. 12. The locations of the mating magnets in the front panel are shown in FIG. 13. To provide for secure grip (and therefore reliable operation), rare earth magnets provide high strength (e.g. neodymium magnets). Some embodiments of the design call for disc magnets approximately 8 mm in diameter and 3 mm thick, with the magnetic field parallel to the axis. In some embodiments, it is sufficient to replace one magnet from each pair with a weaker magnet, or with a piece of magnetic material such as iron or mild steel.
In some embodiments of the systems and platforms disclosed herein, a mechanism for providing for automated door or lid closure on one or more instrument compartments is provided, wherein the mechanism comprises: (a) a closure; (b) a housing which magnetically holds the closure in a first position; and (c) a translation stage which magnetically holds the closure in a second position. In some embodiment, the mechanism further comprises a gasket positioned between the closure and the housing. In some embodiments of the mechanism, the gasket is attached to the closure. In other embodiments, the gasket is attached to the housing. In some embodiments, the closure and housing are substantially opaque, and the gasket creates a substantially light-tight seal between the closure and the housing in the first position. In some embodiments of the mechanism, one or more magnets are positioned to hold the closure onto the housing in the first position. In some embodiments of the mechanism, one or more magnets are positioned to hold the closure onto a first surface of the translation stage in the second position. In some embodiments, the mechanism further comprises two or more pairs of mating locating features to align the closure with the translation stage in the second position. In some embodiments, the mechanism further comprises two or more pairs of mating locating features to align the closure with the housing in the first position. In some embodiments of the mechanism, the pairs of mating locating features comprise conical pins and conical holes. In some embodiments, the housing comprises an optical instrument. In some embodiments, the translation stage includes a sample holder. In some embodiments, the sample holder is designed to hold a microscope slide, a microarray, or a microwell plate. In some embodiments, the closure is not hinged. In some embodiments, the closure is not attached to either the housing or the translation stage through the use of fasteners such as screws or clips. In some embodiments, the closure is not attached to either the housing or the translation stage through the use of an adhesive.
Image Data
The methods, systems, and platforms described herein for counting one or more labeled features on an array may comprise data input, or use of the same. The data input may comprise imaging information and/or images of one or more regions of arrays. The images comprise pixel data, wherein each unit of pixel data may be encoded in, by way of non-limiting examples, 4, 8, 12, 14, 16, 32, 64, 128, 256, or more bits. An image may encompass one or more regions of an array. The spatial resolution of an image may be determined by the spatial resolution of the optical instrument, but in some embodiments of the disclosed methods and systems, spatial resolution may be enhanced by digital image processing schemes based on, by way of non-limiting examples, interpolations, extrapolations, modeling, and/or transforms.
The methods, systems, and platforms described herein for counting one or more labeled features on an array may comprise acquisition and analysis of images of one, two, or more distinct regions on an array. In some embodiments, two or more regions to be imaged may overlap, partially overlap, or not overlap at all. Furthermore, two or more regions to be imaged may be adjacent, or non-adjacent.
The methods, software, systems, and platforms described herein for counting one or more labeled features on an array may comprise acquisition and analysis of images of all or a portion of an array. In some embodiments, the region of an array that is imaged may comprise at least about 1% of the total area of the array. In some embodiments, the region of the array that is imaged image may comprise at least about 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10% or more of the total area of the array. In other embodiments, the region of the array to be imaged may comprise at least about 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, 24%, 25% or more of the total area of the array. In still other embodiments, the region of the array to be imaged may comprise at least about 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70% or more of the total area of the array. In some embodiments, the region of the array to be imaged may comprise at least about 75%, 80%, 85%, 90%, 92%, 95%, 97% or more of the total area of the array.
The methods, software, systems, and platforms described herein for counting one or more labeled features on an array may comprise acquisiton and analysis of images of all or a portion of the features of an array. In some embodiments, the image may encompass between 10% and 100% of the total number of features on the array. In some embodiments, the image may encompass at least 5%, at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or at least 95% of the total number of features on the array. In some embodiments, the image may encompass at most 95%, at most 90%, at most, 80%, at most 70%, at most 60%, at most 50%, at most 40%, at most 30%, at most 20%, at more 10%, or at most 5% of the total number of features on the array. The number of features encompassed by the image may fall within any range bounded by any of these values (e.g. from about 15% to about 90% of the total number of features of the array).
Image Acquisition
The methods, systems, and platforms described herein comprise software for acquiring images from an optical instrument. In some embodiments, e.g. for optical instruments comprising two or more image sensors, the image acquisition may operate in a parallel mode, i.e. where two or more images are acquired simultaneously. Alternatively, the image acquisition may operate in a serial mode, where two or more images are acquired sequentially. In general, image acquisition may be performed in a continuous fashion (i.e., wherein the image is acquired within a single exposure time period) or intermittently (i.e., wherein the image is acquired in a discontinuous fashion, e.g. using two or more separate exposure time periods, wherein in some embodiments two more more images are combined for signal averaging purposes).
In a non-limiting example, an array may comprise 16 wells where an image is formed for each well. The image acquisition module may sequentially read the 16 images. Reading the 16 images can be completed in a continuous time period; or, the system may read a first image followed by analyzing the first image, and then the procedure of image reading and image analysis repeats till the 16th image is analyzed. Alternatively, the image acquisition module may read a pair of images at once, and repeat the reading till all the 16 images are acquired. The 16 images may be read sequentially in a single time period. In some applications, a pair of images may be read, followed by immediate image analyses.
Image Analysis
In general, one of the objectives in performing image processing and analysis is to improve signal-to-noise ratios and quantitation. In an ideal array experiment, labeled features comprising bound target molecules and/or labels would produce a uniform, non-saturated signal level when imaged and non-labeled features would appear uniformly dark, with a signal level of close to zero. In reality, a variety of artifacts due to instrumental and/or assay procedural issues including, but not limited to, stray light, background fluorescence (in the case of fluorescence-based imaging), particulate contaminants, and non-specific binding of assay components, can produce images that hinder one's ability to extract quantitative signal intensity data and make definitive calls as to which features of the array are labeled. Accordingly, the methods, systems, and platforms disclosed herein may comprise software for performing a variety of image processing tasks including, but not limited to, feature location, image orientation correction, background correction, intensity measurement, data scaling, data thresholding, and data analysis functions.
Image orientation and location of features. In some embodiments, fiducial features incorporated into the design of an array are used to orient the image and locate features in an automated fashion using custom image analysis software. By way of non-limiting example, the microarray pattern shown in FIGS. 15 and 16 consists of a 32×32 array of features, where fiducial features in the top and bottom rows permit location of the array in the digital images. The fiducial features are typically arranged in an asymmetric pattern whose orientation is readily identifiable, e.g. fiducial features located in the top row of features in an array such as that depicted in FIG. 16 may comprise a distinctive pattern for which the left and right ends of the row are asymmetric, while the pattern of fiducial features in the bottom row is typically different from that in the top row. This permits easy manual and automatic identification of incorrect placement of the array, and also facilitated detection of imaging problems. In some embodiments, the image may be transformed also transformed so that the apparent orientation of the images corresponds to the orientation as viewed by a user, often referred to as the viewing reference orientation, as shown in FIG. 14 for a specific embodiment of an array designed for use with the methods, systems, and platforms disclosed herein.
Refinement of feature locations. In some embodiments, the measured location of each feature is refined so as to account for array fabrication errors, which can produce offsets of several image pixels. The locations of features obtained during the initial image orientation and feature location step may be used to subdivide the array or array region into analysis windows, for example an array may be divided into 32×32 analysis windows, wherein each analysis window comprises an image area of 12×12 pixels centered on each feature, as shown in FIG. 19. The size of the analysis window used is dependent on the size of the features on the array, and may be any size that is necessary to correctly locate and distinguish between features and background regions on the array. By way of non-limiting examples, the analysis window may be defined as a 5×5, 7×7, 9×9, 15×15, 51×51, or 101×101 pixel area that is centered on the array feature. The position of the feature within the window may be determined on the basis of the signal intensity distribution and clustering of the pixels within the analysis window. The refined location of the feature is calculated as an offset in coordinates X and Y from the site predicted by a perfect rectilinear grid. In some embodiments, distortion of the feature location results due to defects such as dust is avoided by making use of the correlation between printing artifacts between different arrays on the same substrate. Since the printing artifacts are typically consistent, the correction relative to a hypothetical rectilinear grid is also consistent. The feature location optimization results for a given feature are combined across all of the arrays being analyzed, and the median offset is used for subsequent analysis, which greatly decreases noise in the final experimental results.
Local background correction. Once the feature pixel set “S” and background pixel set “B” have been defined for each location in the array (for example, see FIG. 20), the local background is removed via a calculation involving signal intensity and background intensity statistics. Examples of suitable signal and background intensity statistics for use in local background correction calculations include, but are not limited to, the mean, the median, or a ratio of signal-to-background. In some embodiments, following feature location refinement performed as described above, the pixels within the analysis window are assigned to be signal pixels, background pixels, or transitional pixels, i.e. pixels to be disregarded, in subsequent calculations of signal and background intensity statistics (see FIG. 20). In some embodiments of the disclosed methods, local background correction is performed via subtraction in logarithm space, i.e. a calculation that is closely related to a signal-to-background ratio calculation, as illustrated in a non-limiting example below:
Given the 16-bit pixel data measurements for a defined feature and background area, on next calculates a single value S for the signal pixels and a value B for the background pixels respectively. One useful statistic is the median value for each set of pixels, i.e.

    
    
        S=the median of the pixel values for the set of pixels “S”
        B=the median of the pixel values for the set of pixels “B”

Various other statistics could be used in this situation, such as the mean of the set of values, or a nominated percentile within the set. It is not necessary, and may not be optimal, to use the same statistic for both S and B. For example, low data noise and strong separation between “on” and “off” data points can be obtained by using:

        S=the median of the pixel values for the set of pixels “S”, and
        B=the 25th percentile of the pixel values for the set of pixels “B”.

As a further enhancement, the particular percentile used can be a pre-stored and re-configurable parameter stored in a settings file.

The background-corrected intensity statistic for each spot is:

I=log2(16S)−log2(16B)

An example of a scatter plot (intensity statistic vs feature number) and histogram of intensity data are shown in FIG. 21. In this example, the background is corrected for by performing a subtraction of logarithms, such that the intensity metric is related to a ratio of S and B. In some situations, a linear subtraction (e.g. I=S−B) is preferable. Once the background-corrected intensity statistics have been calculated for the compete set of features, the next task is to determine which of the features are labeled (i.e. “on”, or “positive”) and which are non-labeled (i.e. “off” or “negative”). This is accomplished by determining a signal intensity threshold value based on a statistical analysis of the local background-corrected feature intensities, and subsequently counting how many features, k, have background-corrected signal intensities that are larger than this threshold level. The signal intensity threshold may be considered a “dynamic” signal intensity threshold in that the threshold is determined through analysis of the data from the current experiment, and thereby eliminates potential errors due to such factors as instrumental drift and variations in assay procedure.

    
    


Determination of dynamic signal intensity thresholds. In many embodiments of the methods, systems, and platforms disclosed herein, a dynamic signal intensity threshold is determined for one or more regions of an array by performing one or more statistical analyses of the background corrected signal intensity data for the complete set of features. Any of a variety of statistical (or empirical) analysis techniques may be used, including but not limited to, k-means clustering, k-medoids clustering, mixture model statistical analysis, probe reference distribution methods, or empirical analysis based on sorting of background corrected signal intensity values, sorting of pairwise differences in background corrected signal intensity values, etc. In some embodiments, analyses may utilize spatial and/or temporal information collected across multiple analysis windows, across multiple array regions, or over specified periods of time, or combinations thereof, to improve the quality of the analysis and thereby improve the quantitative aspects of the disclosed methods. In some embodiments, other sources of information, including, but not limited to, for example, locations of probes, frequently occurring artifact patterns, previously derived results, literature reports, array manufacturers' suggestions, human knowledge, and/or human guidance may also be integrated into the analysis.
By way of a non-limiting example of threshold determination, in some embodiments of the disclosed methods, the background corrected signal intensity threshold may be determined using an empirical approach (e.g. the “E-Derivative” approach; see FIG. 22) wherein the background corrected signal intensity data for the complete set of array features constitutes a set I={Ii}. The set I is sorted in increasing order to obtain a set of ordered corrected signal intensity values z={zi}={Sort[yi]}. Next, the differences between each sorted array value are calculated to obtain d={d1, d2, . . . , dm}, where di=zi+1−zi. The intensity differences are then smoothed using a “window” whose width is w, to produce a smoothed, sorted array s:




  
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    j
  
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          =
          
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The threshold is T, the point for which the slope of the smoothed, sorted data is steepest (see FIG. 21):

T=max(sj)

The number of features, k, which are “on” (or labeled) is:

k=Σi=1mI[Ii>T]. 

By way of another non-limiting example of threshold determination, in some embodiments the background corrected signal intensity threshold may be determined by fitting the background corrected feature intensity data to two more more assumed distributions (i.e. a “Mixture Model” approach), wherein the assumed distributions comprise normal distributions, uniform distributions, etc. The mixture model approach essentially models the underlying process that generated the data, by assuming that the positive feature intensities are generated from a positive feature distribution with higher average signal intensity, and the negative feature intensities are generated from a negative feature distribution with lower average signal intensity. This approach additionally models the variability in the feature intensities generated by each distribution, which can be useful in cases where the negative feature intensities tend to be much less variable, while the positive feature intensities tends to be much more variable. The choice of the distributions is determined by the shape of the data curve in a background corrected feature intensity histogram. The parameters of the model, e.g. the estimated average intensities for “on” and “off” features and their corresponding variance, are estimated from the data using a method such as the Expectation Maximization algorithm.
By way of another non-limiting example of threshold determination, in some embodiments the background corrected signal intensity threshold may be determined by fitting the background corrected feature intensity data to a model function comprising three assumed distributions (i.e. a “3-Component Model” approach), wherein the assumed distributions comprise a log-normal distribution, Dist1, for the “off” spots, a normal distribution, Dist2, for the “on” spots, and a flat offset FlatLevel. Adjustable parameters for the model include: (i) the number of bins in the starting histogram, (ii) Dist1 amplitude, (iii) Dist1 position, (iv) Dist1 standard deviation, (v) Dist2 amplitude, (vi) Dist2 position, (vii) Dist2 standard deviation, and (viii) FlatLevel. An example fit to histogram data is shown in FIG. 23. One non-limiting example of a method to determine the threshold after fitting feature intensity data to such a distribution is as follows: (i) fit the 3-component distribution to the histogram data, and (ii) set the threshold T by calculating the following values: (1) the intensity tlow where the high-intensity side of the fitted log-normal distribution component drops below 1 (or a defined parameter for comparison), (2) the intensity tsubflat where the high-intensity side of the fitted log-normal distribution component drops below the fitted FlatLevel result, (3) the intensity tsubnorm where the high-intensity side of the fitted log-normal distribution component drops below the value of the fitted normal distribution at that histogram bin, and (4) choosing T=min[tlow, tsubflat, tsubnorm]. Alternative approaches for determining a threshold using a 3-component model approach will be apparent to those of skill in the art. It can be beneficial to calculate starting values of model parameters, to improve the speed and reliability of the modelling process, which can be achieved using methods such as a coarse search to identify the dominant peaks in the histogram, or based on assumptions derived from typical historical data sets.
By way of another non-limiting example of threshold determination, in some embodiments the background corrected signal intensity threshold may be determined using a “Peak Split Fiducials” approach. This approach, which copes well with low-quality data, is described as follows. An initial split of the feature intensity data into high and low intensity groups is made using the scale defined naturally by the spread between “on” (label present) and “off” (label absent) features in the fiducial rows. Then, the histogram peak (after optionally smoothing the data using standard methods such as a moving average filter) is found for each group. The threshold is then determined by examining the spread in the intensity data around the low-intensity group peak. Define upper and lower bounds of fiducial intensity: (i) Foff=[median of OFF fiducials], Fon=[median of ON fiducials], and (iii) Frange=Fon−Foff. Perform an initial split of the data based on the fiducial scale, at the level Splitvalue=Foff+PeakSplit×Frange, where the parameter PeakSplit is a percentage of Frange. Find 2 peaks: (i) Peak4=the intensity peak for which the histogram is a maximum, for all features of intensity less than Splitvalue, (ii) Peak2=the intensity peak for which the histogram is a maximum, for all features of intensity greater than Splitvalue. Calculate the standard deviation, Stdev1, of all the features in the neighbourhood of Peak1, defined as all index features from the lowest intensity up to Peak1+PeakOffsetFraction×(Peak2−Peak1), where PeakOffsetFraction is an adjustable parameter. Set the threshold to the lesser of Tpsf and TLocMin, which are calculated as follows: (i) Tpsf=Peak1+StdevMultiple×Stdev1, where StdevMultiple is a parameter, OR TLocMin=the intensity corresponding to the minimum of a smoothed histogram curve between Peak1 and Tpsf. Similar approaches using different methods for determining the spread around either peak can also be used.
The methods and systems disclosed herein may comprise detecting one or more labeled features within one or more regions on an array. In some embodiments, detecting a labeled feature within a region may comprise comparing the background corrected signal intensity for a feature with a dynamic signal intensity threshold derived through statistical analysis of the background corrected signal intensities for the complete set of features. When the background corrected signal intensity for a given feature is above the threshold, the feature may be classified as a labeled feature. Alternatively, if the background corrected signal intensity for a given feature is below the threshold, the feature may be classified as non-labeled. Application of a background corrected signal intensity threshold to the corrected signal intensity data for the complete set of features thus constitutes a binary transformation of the data to a digital output wherein features are classified as either labeled (“on”) or non-labeled (“off”). Those of skill in the art will recognize that there are many possible variations in the type and order of analysis steps that may be applied to achieve this binary transformation.
Calculation of the absolute number of target molecules in a sample. The absolute number of target molecules in a sample, wherein the target molecules have been labeled in a stochastic fashion as described previously, may be determined using arrays comprising feature sets comprising probes that are specific for the labels in the stochastic label set. Following hybridization or binding of the target molecules or labeled target molecules to the array, the array is imaged and processed as described above, and the number of target molecules, N, in the sample is determined from the number, k, of labeled features based on Poisson distribution statistics:




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      -
      m
    
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where m is the total number of features (i.e. the total number of unique labels in the set of stochastic labels).

Quality metrics. In some embodiments, it is beneficial to include a numerical measure of the quality of the data, to help to gauge the success of an experiment. In some embodiment, this quality measurement may be based on statistics from the feature-by-feature intensity data. One simple quality measurement QSep1 is simply the difference between the means of the positive and negative features intensities, after background correction and scaling, i.e. QSep1=(mean intensity of features having an intensity above the signal intensity threshold)−(mean intensity of features having an intensity below the threshold). In some embodiments, this metric may also incorporate the spread in the intensities of the feature distribution(s) by scaling the difference between means by the standard deviation of each distribution, e.g. QSep2=QSep1/(standard deviation of intensities for feature having intensities below the threshold intensity). Other quality measurements can be constructed based on the separation and breadth of modelled distributions which are fitted to the experimental data. In some embodiments, deviance measurement may be used for a quality metric (FIG. 24); this is a calculation based on the degree of separation between two fitted normal distributions. In some embodiments, it is preferable to empirically determine a dynamic intensity threshold by setting the threshold to a value which maximizes a quality metric.
Confidence intervals. In some embodiments of the methods disclosed herein, it is beneficial to define confidence intervals (see Dube, et al. (2008), PLoS ONE 3(8): e2876 for a more complete description) when specifying estimates of the absolute number of target molecules detected in a sample using the techniques described above. The 95% confidence interval of the estimation of N from stochastic labeling experiments can be derived from k for a single reaction employing a single set of m distinct labels. The 95% confidence interval for N ranges from Nlow to Nhigh, where



  
    
      
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Ratio of the number of copies of a target molecule in two samples. Frequently, researchers seek to compare the expression levels of genes in different samples, by calculating a ratio between gene expression levels in two or more samples. Using calculations such as those described above, it is possible to derive confidence intervals for such ratios where the number of target molecules in each sample are determined using the methods, systems, and platforms as disclosed herein.
Replicate experiments. The benefit of performing replicate experiments, and the proper calculation of associated uncertainties, is illustrated in FIG. 25. While results (blue points) from replicate experiments can simply be combined (blue error bars), calculating the uncertainty from Poisson statistics, wherein one considers the replicates as comprising a larger pool of labels, gives the smaller green error bars illustrated in the figure. The accuracy of this estimation will vary depending on the consistency between replicates, and there is a numerical simplification employed in considering the labels of replicate experiments to be a pool of diverse labels. Therefore, in some embodiments of the disclosed methods, different methods for calculating confidence intervals may be more appropriate at high ratios of k/m.
User Interface
The methods, software, systems, and platforms disclosed herein may comprise a user interface, or use of the same. The user interface may provide one or more inputs from a user. The input from the user interface may comprise instructions for counting the one or more labeled features in a real time mode. The input from the user interface may comprise instructions for counting the one or more features from one or more images. The one or more images may be archived images. The one or more images may be live captured images.
Different platform operators may have their own preferences about the timing to analyze images. One platform operator may want to run the image analyses while live capturing images. Another platform operator may run the image analyses after all the images have been collected. Or, another platform operator may run the image analyses on a set of archived images. These options can be selected via inputs to the user interface.
Digital Processing Device
The methods, software, systems, and platforms disclosed herein may comprise a digital processing device, or use of the same. The digital processing device may comprise one or more hardware central processing units (CPU) that carry out the device's functions. The digital processing device may comprise an operating system configured to perform executable instructions. The digital processing device may be connected to a computer network. The digital processing device may be connected to the Internet such that it accesses the World Wide Web. The digital processing device may be connected to a cloud computing infrastructure. The digital processing device may be connected to an intranet. The digital processing device may be connected to a data storage device.
Suitable digital processing devices may include, by way of non-limiting examples, server computers, desktop computers, laptop computers, notebook computers, sub-notebook computers, netbook computers, netpad computers, set-top computers, handheld computers, Internet appliances, mobile smartphones, tablet computers, personal digital assistants, video game consoles, and vehicles. In some instances, smartphones may be suitable for use in the system described herein. In some instances, select televisions, video players, and digital music players with optional computer network connectivity may be suitable for use in the system described herein. Suitable tablet computers may include those with booklet, slate, and convertible configurations, known to those of skill in the art.
The digital processing device may comprise an operating system configured to perform executable instructions. The operating system may be software, including programs and data, which manages the device's hardware and provides services for execution of applications. Suitable server operating systems may include, by way of non-limiting examples, FreeBSD, OpenBSD, NetBSD®, Linux, Apple® Mac OS X Server®, Oracle® Solaris®, Windows Server®, and Novell® NetWare®. Suitable personal computer operating systems may include, by way of non-limiting examples, Microsoft® Windows®, Apple® Mac OS X®, UNIX®, and UNIX-like operating systems such as GNU/Linux®. The operating system is provided by cloud computing. Suitable mobile smart phone operating systems may include, by way of non-limiting examples, Nokia® Symbian® OS, Apple® iOS®, Research In Motion® BlackBerry OS®, Google® Android®, Microsoft® Windows Phone® OS, Microsoft® Windows Mobile® OS, Linux®, and Palm® WebOS®.
The digital processing device may comprise a storage and/or memory device. The storage and/or memory device may be one or more physical apparatuses used to store data or programs on a temporary or permanent basis. The digital processing device may be a volatile memory and may require power to maintain stored information. The digital processing device may be a non-volatile memory and may retain stored information when the digital processing device is not powered. The non-volatile memory may comprise flash memory. The non-volatile memory may comprise dynamic random-access memory (DRAM). The non-volatile memory may comprise ferroelectric random access memory (FRAM). The non-volatile memory may comprise phase-change random access memory (PRAM). The storage device may include, by way of non-limiting examples, CD-ROMs, DVDs, flash memory devices, magnetic disk drives, magnetic tapes drives, optical disk drives, and cloud computing based storage. The storage and/or memory device may be a combination of devices such as those disclosed herein.
The digital processing device may comprise a display. The display may be used to send visual information to a user. The display may be a cathode ray tube (CRT). The display may be a liquid crystal display (LCD). The display may be a thin film transistor liquid crystal display (TFT-LCD). The display may be an organic light emitting diode (OLED) display. The OLED display may be a passive-matrix OLED (PMOLED) or active-matrix OLED (AMOLED) display. The display may be a plasma display. The display may be a video projector. The display may be a combination of devices such as those disclosed herein.
The digital processing device may comprise an input device to receive information from a user. The input device may be a keyboard. The input device may be a pointing device including, by way of non-limiting examples, a mouse, trackball, track pad, joystick, game controller, or stylus. The input device may be a touch screen or a multi-touch screen. The input device may be a microphone to capture voice or other sound input. The input device may be a video camera to capture motion or visual input. The input device may be a combination of devices such as those disclosed herein.
Non-Transitory Computer Readable Storage Medium
The methods, software, systems, and platforms disclosed herein may comprise one or more non-transitory computer readable storage media encoded with a program including instructions executable by the operating system of an optionally networked digital processing device. A computer readable storage medium may be a tangible component of a digital processing device. A computer readable storage medium may be optionally removable from a digital processing device. A computer readable storage medium may include, by way of non-limiting examples, CD-ROMs, DVDs, flash memory devices, solid state memory, magnetic disk drives, magnetic tape drives, optical disk drives, cloud computing systems and services, and the like. The program and instructions may be permanently, substantially permanently, semi-permanently, or non-transitorily encoded on the media.
Computer Programs (General)
The methods, software, systems, and platforms disclosed herein may comprise at least one computer processor, or use of the same. The computer processor may comprise a computer program. A computer program may include a sequence of instructions, executable in the digital processing device's CPU, written to perform a specified task. Computer readable instructions may be implemented as program modules, such as functions, features, Application Programming Interfaces (APIs), data structures, and the like, that perform particular tasks or implement particular abstract data types. A computer program may be written in various versions of various languages.
The functionality of the computer readable instructions may be combined or distributed as desired in various environments. A computer program may comprise one sequence of instructions. A computer program may comprise a plurality of sequences of instructions. A computer program may be provided from one location. A computer program may be provided from a plurality of locations. A computer program may include one or more software modules. A computer program may include, in part or in whole, one or more web applications, one or more mobile applications, one or more standalone applications, one or more web browser plug-ins, extensions, add-ins, or add-ons, or combinations thereof.
Web Applications
A computer program may include a web application. In light of the disclosure provided herein, those of skill in the art will recognize that a web application may utilize one or more software frameworks and one or more database systems. A web application may be created upon a software framework such as Microsoft®.NET or Ruby on Rails (RoR). A web application may utilize one or more database systems including, by way of non-limiting examples, relational, non-relational, feature oriented, associative, and XML database systems. Suitable relational database systems may include, by way of non-limiting examples, Microsoft® SQL Server, mySQLTM, and Oracle®. Those of skill in the art will also recognize that a web application may be written in one or more versions of one or more languages. A web application may be written in one or more markup languages, presentation definition languages, client-side scripting languages, server-side coding languages, database query languages, or combinations thereof. A web application may be written to some extent in a markup language such as Hypertext Markup Language (HTML), Extensible Hypertext Markup Language (XHTML), or eXtensible Markup Language (XML). A web application may be written to some extent in a presentation definition language such as Cascading Style Sheets (CSS). A web application may be written to some extent in a client-side scripting language such as Asynchronous Javascript and XML (AJAX), Flash® Actionscript, Javascript, or Silverlight®. A web application may be written to some extent in a server-side coding language such as Active Server Pages (ASP), ColdFusion®, Perl, JavaTM, JavaServer Pages (JSP), Hypertext Preprocessor (PHP), PythonTM, Ruby, Tcl, Smalltalk, WebDNA®, or Groovy. A web application may be written to some extent in a database query language such as Structured Query Language (SQL). A web application may integrate enterprise server products such as IBM Lotus Domino. A web application may include a media player element. A media player element may utilize one or more of many suitable multimedia technologies including, by way of non-limiting examples, Adobe® Flash®, HTML 5, Apple® QuickTime®, Microsoft® Silverlight®, JavaTM, and Unity
Mobile Applications
A computer program may include a mobile application provided to a mobile digital processing device. The mobile application may be provided to a mobile digital processing device at the time it is manufactured. The mobile application may be provided to a mobile digital processing device via the computer network described herein.
A mobile application may be created by techniques known to those of skill in the art using hardware, languages, and development environments known to the art. Those of skill in the art will recognize that mobile applications may be written in several languages. Suitable programming languages include, by way of non-limiting examples, C, C++, C#, Featureive-C, JavaTM, Javascript, Pascal, Feature Pascal, PythonTM, Ruby, VB.NET, WML, and XHTML/HTML with or without CSS, or combinations thereof.
Suitable mobile application development environments may be available from several sources. Commercially available development environments include, by way of non-limiting examples, AirplaySDK, alcheMo, Appcelerator®, Celsius, Bedrock, Flash Lite, .NET Compact Framework, Rhomobile, and WorkLight Mobile Platform. Other development environments may be available without cost including, by way of non-limiting examples, Lazarus, MobiFlex, MoSync, and Phonegap. Also, mobile device manufacturers distribute software developer kits including, by way of non-limiting examples, iPhone and iPad (iOS) SDK, AndroidTM SDK, BlackBerry® SDK, BREW SDK, Palm® OS SDK, Symbian SDK, webOS SDK, and Windows® Mobile SDK.
Those of skill in the art will recognize that several commercial forums may be available for distribution of mobile applications including, by way of non-limiting examples, Apple® App Store, AndroidTM Market, BlackBerry® App World, App Store for Palm devices, App Catalog for webOS, Windows® Marketplace for Mobile, Ovi Store for Nokia® devices, Samsung® Apps, and Nintendo® DSi Shop.
Standalone Applications
A computer program may include a standalone application, which may be a program that may be run as an independent computer process, not an add-on to an existing process, e.g., not a plug-in. Those of skill in the art will recognize that standalone applications may be often compiled. A compiler may be a computer program(s) that transforms source code written in a programming language into binary feature code such as assembly language or machine code. Suitable compiled programming languages include, by way of non-limiting examples, C, C++, Featureive-C, COBOL, Delphi, Eiffel, JavaTM, Lisp, PythonTM, Visual Basic, and VB .NET, or combinations thereof. Compilation may be often performed, at least in part, to create an executable program. A computer program may include one or more executable complied applications.
Web Browser Plug-Ins
A computer program may include a web browser plug-in. In computing, a plug-in may be one or more software components that add specific functionality to a larger software application. Makers of software applications may support plug-ins to enable third-party developers to create abilities which extend an application, to support easily adding new features, and to reduce the size of an application. When supported, plug-ins may enable customizing the functionality of a software application. For example, plug-ins are commonly used in web browsers to play video, generate interactivity, scan for viruses, and display particular file types. Those of skill in the art will be familiar with several web browser plug-ins including, Adobe® Flash® Player, Microsoft® Silverlight®, and Apple® QuickTime®. The toolbar may comprise one or more web browser extensions, add-ins, or add-ons. The toolbar may comprise one or more explorer bars, tool bands, or desk bands.
In view of the disclosure provided herein, those of skill in the art will recognize that several plug-in frameworks may be available that enable development of plug-ins in various programming languages, including, by way of non-limiting examples, C++, Delphi, JavaTM, PHP, PythonTM, and VB .NET, or combinations thereof.
Web browsers (also called Internet browsers) may be software applications, designed for use with network-connected digital processing devices, for retrieving, presenting, and traversing information resources on the World Wide Web. Suitable web browsers include, by way of non-limiting examples, Microsoft® Internet Explorer®, Mozilla® Firefox®, Google® Chrome, Apple® Safari®, Opera Software® Opera®, and KDE Konqueror. The web browser may be a mobile web browser. Mobile web browsers (also called mircrobrowsers, mini-browsers, and wireless browsers) may be designed for use on mobile digital processing devices including, by way of non-limiting examples, handheld computers, tablet computers, netbook computers, subnotebook computers, smartphones, music players, personal digital assistants (PDAs), and handheld video game systems. Suitable mobile web browsers include, by way of non-limiting examples, Google® Android® browser, RIM BlackBerry® Browser, Apple® Safari®, Palm® Blazer, Palm® WebOS® Browser, Mozilla® Firefox® for mobile, Microsoft® Internet Explorer® Mobile, Amazon® Kindle® Basic Web, Nokia® Browser, Opera Software® Opera® Mobile, and Sony® PSPTM browser.
Software Modules (General)
The methods, software, systems, and platforms disclosed herein may comprise one or more softwares, servers, and database modules, or use of the same. In view of the disclosure provided herein, software modules may be created by techniques known to those of skill in the art using machines, software, and languages known to the art. The software modules disclosed herein may be implemented in a multitude of ways. A software module may comprise a file, a section of code, a programming feature, a programming structure, or combinations thereof. A software module may comprise a plurality of files, a plurality of sections of code, a plurality of programming features, a plurality of programming structures, or combinations thereof. The one or more software modules may comprise, by way of non-limiting examples, a web application, a mobile application, and a standalone application. Software modules may be in one computer program or application. Software modules may be in more than one computer program or application. Software modules may be hosted on one machine. Software modules may be hosted on more than one machine. Software modules may be hosted on cloud computing platforms. Software modules may be hosted on one or more machines in one location. Software modules may be hosted on one or more machines in more than one location.
Databases
The methods, software, systems, and platforms disclosed herein may comprise one or more databases, or use of the same. In view of the disclosure provided herein, those of skill in the art will recognize that many databases may be suitable for storage and retrieval of imaging information. Suitable databases may include, by way of non-limiting examples, relational databases, non-relational databases, feature oriented databases, feature databases, entity-relationship model databases, associative databases, and XML databases. A database may be internet-based. A database may be web-based. A database may be cloud computing-based. A database may be based on one or more local computer storage devices.
EXAMPLES
The following illustrative examples are representative of specific embodiments of the methods, systems, and platforms described herein, but are not meant to be limiting in any way.
Example 1
Optical Instrument
FIG. 1 shows one embodiment of the optical instrument. This embodiment was used for simultaneously imaging 2 adjacent wells of a 16-well microscope slide. Each well contained 1024 (32×32) features, also called spots, which may be labeled with fluorescence. A spot diameter was approximately 80 microns. Center-to-center distance between adjacent spots was 161 microns. The purpose of the instrument was to determine the brightness of each spot. FIG. 1E shows the translation stage system 105, imaging system 106, and illumination system 107. The translation stage system contained a single-axis translation stage which was constructed from a Misumi model SSELBW9-170 recirculating ball slide driven by a Haydon Kerk 26000-series linear actuator. A holder for a 16-well microscope slide was mounted on the translation stage. The linear actuator was controlled by a Peter Norberg Consulting model BC2D20-0700 motion controller. FIG. 1G shows a USB hub 112, custom circuit board 113, and a motion controller 114. The motion controller and the CCD camera were USB devices. The USB hub allowed communication between a computer and the instrument to take place over a single USB cable. The custom circuit board contained a Luxdrive model 3021-D-E-1000 LED driver. The custom circuit board contained a logic chip to synchronize the LED with the CCD camera (turn the LED on when the CCD camera starts an exposure and off when the CCD camera finishes an exposure) and to prevent the LED from turning on when the instrument's door is open.
Example 2
Imaging System
An embodiment of an imaging system is illustrated in FIG. 2. Light emitted by dye molecules on a surface of the support 205 was collimated by an achromatic cemented doublet lens 204, filtered by a bandpass filter 203, and focused by a camera lens 202 onto the sensor 201 of a CCD camera. Lens 204 (Edmund Optics model 47640) had a focal length of 85 mm and a diameter of 25 mm. Filter 203 (Semrock model FF01-593/40-25) was an emission bandpass filter for use with cy3 or phycoerythrin dye. Lens 202 (Fujinon model HF25HA-1B) has a focal length of 25 mm. Lens 202 was a multi-element lens, but it is shown in FIG. 2 as an infinitesimally thin single-element lens because the design details of the multi-element lens were proprietary to Fujinon. The adjustable aperture stop of lens 202 was set to 2.8. The CCD camera (Point Grey Research model CMLN-13S2M-CS) had 1296×964 pixels and a pixel size of 3.75 microns. In this embodiment only the central 1280×640 pixels were used. The camera's plastic housing was removed and the camera's circuit board was cooled by a small fan. Lenses 204 and 202 formed a finite-conjugate imaging system with a magnification of 0.3.
Example 3
Illumination System
An embodiment of an illumination system is illustrated in FIG. 3. Light emitted by light source 301 was collimated by lens 302 and then passed through aperture 303, bandpass filter 304, and lenses 305, 306, and 307, before reaching sample 308. Light source 301 (LedEngin model LZ4-40G100) was an LED with a peak emission wavelength of approximately 525 nm. Lens 302 (Thorlabs model ACL2520-A) was an aspheric lens with a diameter of 25 mm and a focal length of 20 mm. Aperture 303 (Fotofab custom part) was a rectangular hole (19 mm×7.5 mm) in a 25-mm-diameter steel disk. Filter 304 (Semrock model FF01-531/40-25) was an excitation bandpass filter for use with cy3 or phycoerythrin dye. Lenses 305, 306, and 307 were plano-convex lenses with diameters of 25 mm and focal lengths of 60 mm. Lenses 301 and 302 formed a finite-conjugate imaging system with a magnification of 3 and imaged light source 301 onto the pupils of lenses 306 and 307. Lenses 306 and 307 formed a finite-conjugate imaging system with a magnification of 1 and imaged aperture 303 onto sample 308. The illumination system was tilted at 45 degrees with respect to sample 308. The illuminated area was approximately 19 mm×10.6 mm, where 10.6 mm (=7.5 mm/cosine (45 degrees)).
Example 4
Reference Probe Preparation
The purpose of this experiment was to illustrate the use of an ad hoc method to count the number of hybridizations taking place on an array. This example used probes that the specific DNA sequences attached to an array. The 32×32 feature arrays used in this experiment contain 960 different measure spots along with 32 positive control probes and 32 negative control probes (see FIGS. 15 and 16). The 32 positive control probes were used to ensure actual binding can occur by using stock oligonucleotide, while the 32 negative control probes contained empty spots with no probes at all. In the image analysis step, we considered a probe to have intensity above the set intensity threshold, then we referred to the probe as a positive probe, while if the probe intensity was below the set intensity threshold, we referred to the probe as a negative feature. Positive probes were assumed to measure whether there was a significant amount of corresponding complementary oligonucleotide in the sample, while negative features represented absent oligonucleotides. The positive probes were otherwise referred to as labels, meaning we can count up to 960 unique labels or barcodes, to measure 960 copies of oligonucleotides in the sample, which can then be further generalized to predict the actual amount of oligonucleotides in the original sample. Depending on the experiment, out of the M total labels, or 960 total labels, we could calculate the total number of copies, N, of the oligonucleotides in the sample, by predicting N from the actual observed unique barcodes or number of positive probes, k.
Example 5
Threshold Computation
The purpose of this experiment was to demonstrate one method to compute a threshold for discriminating between labeled and non-labeled features on an array.

    
    
        I. Set ILL, intensity lower limit, IUL, intensity upper limit, and w, window size.
        II. Obtain a set of feasible threshold intensities, y={yi:ILL<Ii<IUL}
        III. Sort y in increasing order to obtain y*.
        IV. Calculate d={d1, d2, di, . . . , dm}, where di=yi+1*−yi*.
        V. Calculate a gap statistic for each of the observed intensities:
    
    






  
    x
    j
  
  =
  
    
      
        ∑
        
          i
          =
          
            j
            -
            w
          
        
        
          j
          +
          w
        
      
      ⁢
      
        d
        i
      
    
    
      
        2
        ⁢
        
          
        
        ⁢
        w
      
      +
      1
    
  




    
    
        VI. Identify the threshold c, such that c=max(xj)
        VII. Count the number of spots, k, above the threshold c, where k=Σi=1mI[yi>c].
        VIII. Given a number of simulations desired, nsim, perform the following procedure nsim times: Randomly select m values with replacement from y={y1, y2, . . . , ym} to obtain ysim. Then repeat Step I-VII with ysim to obtain a final count.
        IX. Calculate {circumflex over (σ)}k the standard deviation of the nsim simulated counts.
        X. Calculate the 95% CI for the count as:

[k−1.96{circumflex over (σ)}k,k+1.96{circumflex over (σ)}k].

        Note that in order to obtain the true estimate of the molecule count in the sample, we needed to transform by:
    
    






  N
  =
  
    
      -
      m
    
    *
    
      log
      ⁡
      
        (
        
          1
          -
          
            k
            m
          
        
        )
      
    
  




    
    
        and similarly, for the 95% CI upper and lower values, where m is the total number of features on the array.
    
    


Example 6
Detection of Kan Genes
The purpose of this experiment was to determine the count of kan genes in a sample. The sample containing the kan genes was hybridized to an array. FIG. 4A displays a region of the array acquired from the imaging system. The bright intensity at a spot was correlated with a higher probability of a gene being present at the spot. The image analysis software examined the statistics of the intensity distribution, such as deviance, skewness, kurtosis, and median. These statistics provided guidance for the software to automatically choose the best method to detect the presence of kan genes. In this example, a mixture model algorithm was used to determine the intensity threshold to be 6.6, which optimally divided the intensity distribution into “on” and “off” domains, as shown in FIG. 4B.
Example 7
Titration Experiment
The purpose of this experiment was to detect the presence of molecular hybridization in a titration experiment. After obtaining the intensity measurements of a region, the intensity distribution was computed and is shown in FIG. 5. A person with ordinary skill can identify two modes in the distribution; however, it was very difficult to determine the precise value of the threshold. The invented software automated the task of determining the signal intensity threshold, and determined that an intensity value of 6.02 provides the optimal threshold for distinguishing between labeled and non-labeled features.
Example 8
Background Adjustment
The purpose of this experiment was to demonstrate use of one background subtraction method to process images. FIG. 6A shows an acquired image with pronounced artifacts. A systematic background subtraction was performed to reduce noise. We defined an analysis window centered on a spot. The software then calculated the mean spot intensity, S, spot standard deviation σS, number of spot pixels nS, background mean B, background standard deviation σB, and number of background pixels nB. Then, the software calculated the log 2 background subtracted intensity statistic for each spot:



  
    I
    =
    
      
        
          
            log
            2
          
          ⁡
          
            (
            
              16
              ⁢
              
                
              
              ⁢
              
                S
                _
              
            
            )
          
        
        -
        
          
            log
            2
          
          ⁡
          
            (
            
              16
              ⁢
              
                
              
              ⁢
              
                B
                _
              
            
            )
          
        
      
      
        
          
            
              τ
              S
              2
            
            
              n
              S
            
          
          +
          
            
              τ
              B
              2
            
            
              n
              B
            
          
        
      
    
  




  where




  
    
      τ
      S
    
    =
    
      
        
          log
          2
        
        ⁡
        
          (
          
            16
            ⁢
            
              (
              
                
                  σ
                  S
                
                +
                
                  S
                  _
                
              
              )
            
          
          )
        
      
      -
      
        
          log
          2
        
        ⁡
        
          (
          
            16
            ⁢
            
              
            
            ⁢
            
              σ
              S
            
          
          )
        
      
    
  




  
    
      τ
      B
    
    =
    
      
        
          log
          2
        
        ⁡
        
          (
          
            16
            ⁢
            
              (
              
                
                  σ
                  B
                
                +
                
                  B
                  _
                
              
              )
            
          
          )
        
      
      -
      
        
          log
          2
        
        ⁡
        
          (
          
            16
            ⁢
            
              
            
            ⁢
            
              σ
              B
            
          
          )
        
      
    
  



FIGS. 6B and 6C show the intensity distributions before and after background adjustment, respectively, demonstrating that background correction enhances the ability of the software to correctly evaluate the presence of the labeled features on the array.

Example 9
Alternative Background Correction
The purpose of this experiment was an alternative way to adjust background. We defined an analysis window centered on a spot. The software then calculated the median spot intensity {tilde over (S)} and median local background intensity {tilde over (B)}. Then, the software calculated the log 2 background subtracted intensity statistic for each spot:

I=log2(16{tilde over (S)})−log2(16{tilde over (S)}).

Example 10
Pixel 16 Cartridge and Custom Microarray
This example illustrated one embodiment of an array for use with the disclosed methods, systems, and platforms in performing stochastic labeling experiment.
The Pixel 16 cartridge consists of (i) an epoxysilane functionalized glass slide serving as an array substrate, (ii) 16 copies of the custom microarray described in FIGS. 14-16, printed on the functionalized surface of the slide, and (iii) a polymer well frame affixed to the printed side of the slide which serves to define 16 wells which are fluidically separate and in register with the array pattern. The well frame is affixed to the slide following array printing using a die-cut double-sided adhesive.
Custom DNA microarray layout. The microarray pattern consists of a 32×32 array of spots as shown in FIGS. 15 and 16. Fiducial spots in the top and bottom rows permit location of the array in the scanned images. Also, the fiducial spots are arranged in an asymmetric pattern whose orientation is readily identifiable: the top row has a distinctive pattern whose ends are distinct, and the bottom row is different from the top row. This permits easy manual and automatic identification of incorrect placement of the Pixel 16, and also facilitates detection of imaging problems. The remaining 960 spots are each associated with one of the unique probe sequences listed in Table 1.
Oligonucleotide sequences and solution components. Oligonucleotide solutions are provided for preparation of printing solutions in 96-well microplates. Concentration as supplied is 100 μM in H2O. Dilution prior to printing is performed using the Tecan GenMate. Dilution is 880 μL of stock oligo+1320 μL of buffer. The dilution buffer used is 250 mM sodium phosphate with 0.00833% sarcosyl. Buffer is filtered using a 0.2 μm filter. Three sets of plates are prepared in each probe preparation operation. Tips are discarded after each source plate. The final dispensed solution is 40 μM DNA in 150 mM sodium phosphate with 0.005% sarcosyl. The fiducial oligo is supplied at 500 μM in H2O. The fiducial oligonucleotide sequence is: 5′-/5AmMC6/TCC TGA ACG GTA GCATCT TGA CGA C-3′ (SEQ ID NO: 1), 25 bases, 5′ Amino Modifier C6, standard desalting; supplied at 500 μM in H2O. The fiducial is diluted by mixing 176 μL of fiducial, 704 μL of water, and 1320 μL of buffer. The final fiducial mixture is 40 μM in 150 mM sodium phosphate with 0.005% sarcosyl.
Table of oligonucleotide sequences. The oligonucleotide sequences for the 960 probe sequences (i.e. the sequences that are complementary to the set of stochastic labeling sequences used in molecular counting experiments) are listed in Table 1.







TABLE 1







Oligonucleotide Probe Sequences for Custom Microarray


(Table 1 discloses SEQ ID NOS 2-961, respectively, in order of appearance)




















Calc'd



Plate
IDT
Well
Seq

IDT Mfg
Molec.



Name
Ref. #
Pos.
Name
Sequence
ID
Weight
Tm

















AJ_P1
85652789
A01
AJ_1
/5AmMC6/CCC AAA GGG TAC CAG
106534039
8795
61.7






AGC TTA AGG TCA A





 


AJ_P1
85652790
A02
AJ_2
/5AmMC6/CCC AAA GCG TTA AGG
106534040
8727
59.7






TTT CTT GTC ACA A





 


AJ_P1
85652791
A03
AJ_3
/5AmMC6/CCC AAG TCG TAC GAA
106534041
8675
61.8






CTC ACC ACA TGA A





 


AJ_P1
85652792
A04
AJ_4
/5AmMC6/CCC AAA CTT GTT CCC TTG
106534042
8672
60.3






AGA CCA GTA A





 


AJ_P1
85652793
A05
AJ_5
/5AmMC6/CCC AAG ACT TCT ACC
106534043
8657
60.7






CTA GGT TCC AGA A





 


AJ_P1
85652794
A06
AJ_6
/5AmMC6/CCC AAC CAG ACT TGG
106534044
8755
62.3






GTA CGT GAA ACA A





 


AJ_P1
85652795
A07
AJ_7
/5AmMC6/CCC AAC GAC TGG TTC
106534045
8786
62.3






TGA AGT GGA ACA A





 


AJ_P1
85652796
A08
AJ_8
/5AmMC6/CCC AAT TTA GCT TCG
106534046
8712
60.4






TGA GTC AGA CCA A





 


AJ_P1
85652797
A09
AJ_9
/5AmMC6/CCC AAC TCG AAG AGT
106534047
8752
59.8






GGT CAG TCT TTA A





 


AJ_P1
85652798
A10
AJ_10
/5AmMC6/CCC AAT CGC AAG GAG
106534048
8745
58.4






ACA TAG TCT TTA A





 


AJ_P1
85652799
A11
AJ_11
/5AmMC6/CCC AAG TCC TAG TGA
106534049
8761
60






GAG CAA CGT TTA A





 


AJ_P1
85652800
A12
AJ_12
/5AmMC6/CCC AAG GAA CCT ACT
106534050
8697
61.4






GTC CTT GTC AGA A





 


AJ_P1
85652801
B01
AJ_13
/5AmMC6/CCC AAA CTA GAA GAC
106534051
8779
59.7






GAG TTC GAG TCA A





 


AJ_P1
85652802
B02
AJ_14
/5AmMC6/CCC AAG GAC ATA CTC
106534052
8699
60






AAC GTA GCT CAA A





 


AJ_P1
85652803
B03
AJ_15
/5AmMC6/CCC AAG GCA TTT GCA
106534053
8690
61.9






ACC TCA CAT GAA A





 


AJ_P1
85652804
B04
AJ_16
/5AmMC6/CCC AAG TAC CCA TCC
106534054
8666
61.3






ACT GTC GAG TAA A





 


AJ_P1
85652805
B05
AJ_17
/5AmMC6/CCC AAA GCG TTT GTG
106534055
8745
59.4






TAA CAG ACC ATA A





 


AJ_P1
85652806
B06
AJ_18
/5AmMC6/CCC AAA TGG TCT GGT
106534056
8737
62.3






TCG ACA GTC ACA A





 


AJ_P1
85652807
B07
AJ_19
/5AmMC6/CCC AAG AGG TAC AAC
106534057
8795
60.6






GAC TCT AGG GTA A





 


AJ_P1
85652808
B08
AJ_20
/5AmMC6/CCC AAG AAC TTC TAC
106534058
8687
58.9






TTG CTT CGT GAA A





 


AJ_P1
85652809
B09
AJ_21
/5AmMC6/CCC AAG CAC TTT CTG
106534059
8687
58.8






TTA ACT AGC TGA A





 


AJ_P1
85652810
B10
AJ_22
/5AmMC6/CCC AAG AAC CTC TCT
106534060
8672
58.6






CTA GTG CTA GTA A





 


AJ_P1
85652811
B11
AJ_23
/5AmMC6/CCC AAG CCT TTA AGC
106534061
8681
60.4






CTA AAG TCC TGA A





 


AJ_P1
85652812
B12
AJ_24
/5AmMC6/CCC AAT CTG GTA GCT
106534062
8672
60.3






CAA CAT CCT TGA A





 


AJ_P1
85652813
C01
AJ_25
/5AmMC6/CCC AAA GGA CTC CAT
106534063
8795
61.8






GGA GAA GTG TCA A





 


AJ_P1
85652814
C02
AJ_26
/5AmMC6/CCC AAG AAC CCT TTC
106534064
8657
62.4






TGG AAG CTT CCA A





 


AJ_P1
85652815
C03
AJ_27
/5AmMC6/CCC AAA TTC GCT TCC
106534065
8712
60.1






TAG TAG TGG ACA A





 


AJ_P1
85652816
C04
AJ_28
/5AmMC6/CCC AAC CGT ACG AAG
106534066
8681
59.4






ACC TAG TTT CTA A





 


AJ_P1
85652817
C05
AJ_29
/5AmMC6/CCC AAT CAC GAA GAG
106534067
8745
58.4






AGT CAC TGT TTA A





 


AJ_P1
85652818
C06
AJ_30
/5AmMC6/CCC AAG AAA CAT AAA
106534068
8763
59.3






CTC GAG TTG CGA A





 


AJ_P1
85652819
C07
AJ_31
/5AmMC6/CCC AAC CAG TTA CGT
106534069
8752
60.7






GAG TGT TGC TAA A





 


AJ_P1
85652820
C08
AJ_32
/5AmMC6/CCC AAA CTC GTG ACT
106534070
8672
60.5






CCT GTT TCA GAA A





 


AJ_P1
85652821
C09
AJ_33
/5AmMC6/CCC AAC GGT TGA AGA
106534071
8779
60.6






GAC TCC TGA AAA A





 


AJ_P1
85652822
C10
AJ_34
/5AmMC6/CCC AAA TTG CTC TGG
106534072
8705
59.8






TCA CAT CGA AAA A





 


AJ_P1
85652823
C11
AJ_35
/5AmMC6/CCC AAC AGG ACT TGT
106534073
8752
60.7






GCT ACG TGT TAA A





 


AJ_P1
85652824
C12
AJ_36
/5AmMC6/CCC AAA TTT CGT GTG
106534074
8672
61.9






TCA ACC ATG CCA A





 


AJ_P1
85652825
D01
AJ_37
/5AmMC6/CCC AAC GTG AAG GCT
106534075
8754
59.7






TAA CAA CAT TGA A





 


AJ_P1
85652826
D02
AJ_38
/5AmMC6/CCC AAT GAA CAC AAC
106534076
8723
59






TAC GAA GCT GTA A





 


AJ_P1
85652827
D03
AJ_39
/5AmMC6/CCC AAA CTT CCG TTG
106534077
8687
58.7






TTA CTA GTC GAA A





 


AJ_P1
85652828
D04
AJ_40
/5AmMC6/CCC AAG GAG TAC AAG
106534078
8786
61






CTT CCT AGG GTA A





 


AJ_P1
85652829
D05
AJ_41
/5AmMC6/CCC AAG TGC TAA ACT
106534079
8687
58.8






GCT CTT TAC GTA A





 


AJ_P1
85652830
D06
AJ_42
/5AmMC6/CCC AAA GAA ACT GCA
106534080
8705
59.5






TCT CCT TTG GAA A





 


AJ_P1
85652831
D07
AJ_43
/5AmMC6/CCC AAG GAC TAA GTT
106534081
8666
61.4






CCA CTC ACC TGA A





 


AJ_P1
85652832
D08
AJ_44
/5AmMC6/CCC AAA GTT GTC TGG
106534082
8752
60.5






TTC ACT CGA GAA A





 


AJ_P1
85652833
D09
AJ_45
/5AmMC6/CCC AAC GTT CTA AGT
106534083
8727
59.2






TTG CTT CGA AGA A





 


AJ_P1
85652834
D10
AJ_46
/5AmMC6/CCC AAC TAA AGG TTG
106534084
8730
61.5






TGC ATC CAA GCA A





 


AJ_P1
85652835
D11
AJ_47
/5AmMC6/CCC AAA GGC TTC ACG
106534085
8696
59.4






ACA TGT CAT TTA A





 


AJ_P1
85652836
D12
AJ_48
/5AmMC6/CCC AAC TGC TAG GTT
106534086
8681
59.7






CCT ACA CAA GTA A





 


AJ_P1
85652837
E01
AJ_49
/5AmMC6/CCC AAA TCA GTA GCT
106534087
8699
59.8






ACA CCA CAG GTA A





 


AJ_P1
85652838
E02
AJ_50
/5AmMC6/CCC AAG ACT GCA AGC
106534088
8690
60.6






TCA CTA CAT TGA A





 


AJ_P1
85652839
E03
AJ_51
/5AmMC6/CCC AAG CTA CTC CTC
106534089
8690
58.9






TAA GAG CAT AGA A





 


AJ_P1
85652840
E04
AJ_52
/5AmMC6/CCC AAT GGA ACG CTA
106534090
8779
60.9






AGG TGT AAA CCA A





 


AJ_P1
85652841
E05
AJ_53
/5AmMC6/CCC AAG AAA CTA ACC
106534091
8690
61.5






TTG GCT TGC CAA A





 


AJ_P1
85652842
E06
AJ_54
/5AmMC6/CCC AAC CAT TAG ACC
106534092
8672
61.3






TTG TGT TGC CAA A





 


AJ_P1
85652843
E07
AJ_55
/5AmMC6/CCC AAG GTC TGA CAG
106534093
8777
61.7






TAG GTG TTC CAA A





 


AJ_P1
85652844
E08
AJ_56
/5AmMC6/CCC AAT TTC GCA AGC
106534094
8696
59.7






CTT GGT ACA TAA A





 


AJ_P1
85652845
E09
AJ_57
/5AmMC6/CCC AAG TTT CTA GCC
106534095
8657
61.2






TAC CAC TAC GGA A





 


AJ_P1
85652846
E10
AJ_58
/5AmMC6/CCC AAA TAG ACC TAA
106534096
8779
60.1






CGG AAG CTG TGA A





 


AJ_P1
85652847
E11
AJ_59
/5AmMC6/CCC AAG GAG TCA TCC
106534097
8712
60.7






ATG CAT CTT TGA A





 


AJ_P1
85652848
E12
AJ_60
/5AmMC6/CCC AAC CGT ACT AGC
106534098
8721
60.5






TTG GGT TAA ACA A





 


AJ_P1
85652849
F01
AJ_61
/5AmMC6/CCC AAA AAG GCT AGC
106534099
8696
59






CTT CTG ACT TTA A





 


AJ_P1
85652850
F02
AJ_62
/5AmMC6/CCC AAA GAG CTC TGC
106534100
8705
58.8






ACT ACA AGT TTA A





 


AJ_P1
85652851
F03
AJ_63
/5AmMC6/CCC AAC AGC TAA CGG
106534101
8779
60






TAG TAA AGG TCA A





 


AJ_P1
85652852
F04
AJ_64
/5AmMC6/CCC AAA GCT TTC CGT TTC
106534102
8696
60






AAA GTG ACA A





 


AJ_P1
85652853
F05
AJ_65
/5AmMC6/CCC AAG TCC ATG CTT
106534103
8690
61.3






CCA GTG ACA AAA A





 


AJ_P1
85652854
F06
AJ_66
/5AmMC6/CCC AAG TAG CTT TGC
106534104
8687
58.4






TCT ACT CGT AAA A





 


AJ_P1
85652855
F07
AJ_67
/5AmMC6/CCC AAC TTC GAA CTA
106534105
8779
59.7






AGG AGT AGA GCA A





 


AJ_P1
85652856
F08
AJ_68
/5AmMC6/CCC AAT TCA GTC CTA
106534106
8770
58.5






GAG GAG AGA CTA A





 


AJ_P1
85652857
F09
AJ_69
/5AmMC6/CCC AAT AGG TCT GTC
106534107
8672
59.6






TTA CCC AAC GTA A





 


AJ_P1
85652858
F10
AJ_70
/5AmMC6/CCC AAC GTG AGG AAA
106534108
8770
60.7






GTT CTG CTA ACA A





 


AJ_P1
85652859
F11
AJ_71
/5AmMC6/CCC AAG TTG GCA ACT
106534109
8712
60.7






TGC TCT CTA AGA A





 


AJ_P1
85652860
F12
AJ_72
/5AmMC6/CCC AAG ACA TCT CTC
106534110
8690
59






TCA GAG CTA GAA A





 


AJ_P1
85652861
G01
AJ_73
/5AmMC6/CCC AAT TTC GCA TGT CTC
106534111
8672
60.9






ATC AGG ACA A





 


AJ_P1
85652862
G02
AJ_74
/5AmMC6/CCC AAA GCC TTC CTT
106534112
8721
60.6






GGT ACT GAA AGA A





 


AJ_P1
85652863
G03
AJ_75
/5AmMC6/CCC AAA CTT GCC TTG
106534113
8696
59.9






CGT ACT GTA AAA A





 


AJ_P1
85652864
G04
AJ_76
/5AmMC6/CCC AAC ACT TTG TAC
106534114
8761
59.7






GGT AGA GAC GTA A





 


AJ_P1
85652865
G05
AJ_77
/5AmMC6/CCC AAG TTT CCA TCA
106534115
8681
61.2






ACC GAA GCT TGA A





 


AJ_P1
85652866
G06
AJ_78
/5AmMC6/CCC AAG CAT TAC CAA
106534116
8699
61






ACT GGA ACC TGA A





 


AJ_P1
85652867
G07
AJ_79
/5AmMC6/CCC AAC CGT ACA ACT
106534117
8687
59.7






TGT TCG TTT GAA A





 


AJ_P1
85652868
G08
AJ_80
/5AmMC6/CCC AAC AGC TAG TAG
106534118
8690
60.7






CAC ACC ATT TGA A





 


AJ_P1
85652869
G09
AJ_81
/5AmMC6/CCC AAC CTC ACG AAA
106534119
8690
61.2






GCA TCA TTG TGA A





 


AJ_P1
85652870
G10
AJ_82
/5AmMC6/CCC AAA CAA AGT GAG
106534120
8739
60.5






GTC ATC TCG ACA A





 


AJ_P1
85652871
G11
AJ_83
/5AmMC6/CCC AAG AAA CCT TCT
106534121
8721
59.9






TGT AGG ACT CGA A





 


AJ_P1
85652872
G12
AJ_84
/5AmMC6/CCC AAA AGC CTA AGC
106534122
8696
58.9






TCT GTC AGT TTA A





 


AJ_P1
85652873
H01
AJ_85
/5AmMC6/CCC AAA CGT TCC CTT
106534123
8681
60.9






CAT GTC GAA AGA A





 


AJ_P1
85652874
H02
AJ_86
/5AmMC6/CCC AAG TAG CAC TGA
106534124
8699
60.7






CAC CAA GCA TTA A





 


AJ_P1
85652875
H03
AJ_87
/5AmMC6/CCC AAG TTT GAC TCC
106534125
8657
62.2






AAG CCT ACG TCA A





 


AJ_P1
85652876
H04
AJ_88
/5AmMC6/CCC AAA CCG TTG GTG
106534126
8770
61.2






AAG CCT TAA AGA A





 


AJ_P1
85652877
H05
AJ_89
/5AmMC6/CCC AAG CCT ACA CCT
106534127
8675
61.9






TCA GTG AAC AGA A





 


AJ_P1
85652878
H06
AJ_90
/5AmMC6/CCC AAC AGC TCA AGC
106534128
8723
59.2






AGT TAG TAA ACA A





 


AJ_P1
85652879
H07
AJ_91
/5AmMC6/CCC AAT ACG CAA GCA
106534129
8745
59.3






TGT AGG TTT ACA A





 


AJ_P1
85652880
H08
AJ_92
/5AmMC6/CCC AAC ACG AGT CGT
106534130
8727
59.3






TAG TTG TTT CAA A





 


AJ_P1
85652881
H09
AJ_93
/5AmMC6/CCC AAT TCG GAA GAC
106534131
8690
59.6






CTA CTA ACC TGA A





 


AJ_P1
85652882
H10
AJ_94
/5AmMC6/CCC AAA GGT CTC TAC
106534132
8763
58.2






GAA AGG AAC ATA A





 


AJ_P1
85652883
H11
AJ_95
/5AmMC6/CCC AAG TGC TAG ACG
106534133
8761
60.6






TCT GTG TCA AAA A





 


AJ_P1
85652884
H12
AJ_96
/5AmMC6/CCC AAA CCA GTG GAC
106534134
8657
61






TTC TCT CCT AGA A





 


AJ_P2
85652886
A01
AJ_97
/5AmMC6/CCC AAC ATG TAG GAG
106534135
8746
61.3






ACG TAG TTC CCA A





 


AJ_P2
85652887
A02
AJ_98
/5AmMC6/CCC AAG AAC TCT CTG
106534136
8752
60.2






GTT AGG CTT GAA A





 


AJ_P2
85652888
A03
AJ_99
/5AmMC6/CCC AAG GAC ATC CAC
106534137
8675
62.1






ATC GTC TGA CAA A





 


AJ_P2
85652889
A04
AJ_100
/5AmMC6/CCC AAA CTT GTT GGG
106534138
8736
59.8






TTC AGC TAA CAA A





 


AJ_P2
85652890
A05
AJ_101
/5AmMC6/CCC AAC ACG TGT CCT
106534139
8681
61.2






GTC ATG TCA AAA A





 


AJ_P2
85652891
A06
AJ_102
/5AmMC6/CCC AAT CGG AAA CCA
106534140
8705
59.4






ACG TTA GCT TTA A





 


AJ_P2
85652892
A07
AJ_103
/5AmMC6/CCC AAG GAC TTA GGT
106534141
8777
61.4






ACC TGT TCG GAA A





 


AJ_P2
85652893
A08
AJ_104
/5AmMC6/CCC AAG ACT TAA CAA
106534142
8739
60.1






CCT GTG ACG AGA A





 


AJ_P2
85652894
A09
AJ_105
/5AmMC6/CCC AAG TTA ACA TGC
106534143
8779
60.7






AGA CGA ACG GTA A





 


AJ_P2
85652895
A10
AJ_106
/5AmMC6/CCC AAG CGT ACA ACT
106534144
8687
58.9






CTT GTC AGT TTA A





 


AJ_P2
85652896
A11
AJ_107
/5AmMC6/CCC AAG TAA CAC CTT
106534145
8746
61.9






CTG AGC AGT GGA A





 


AJ_P2
85652897
A12
AJ_108
/5AmMC6/CCC AAG ACC TAC CTC
106534146
8675
60.7






TCA GGA ACA GTA A





 


AJ_P2
85652898
B01
AJ_109
/5AmMC6/CCC AAA CCT GAC CTT
106534147
8739
59.9






AGG AAG AGC ATA A





 


AJ_P2
85652899
B02
AJ_110
/5AmMC6/CCC AAC AAA GTT TGT
106534148
8736
59.3






CTC AGT TAG CGA A





 


AJ_P2
85652900
B03
AJ_111
/5AmMC6/CCC AAC GGT AGC ATT
106534149
8752
60.5






GTT CCT GTA GAA A





 


AJ_P2
85652901
B04
AJ_112
/5AmMC6/CCC AAC TAG GTT TGT TCT
106534150
8727
58






AGA CAG CTA A





 


AJ_P2
85652902
B05
AJ_113
/5AmMC6/CCC AAG TCT CTA CGT
106534151
8681
59.8






TCC ATC GAA AGA A





 


AJ_P2
85652903
B06
AJ_114
/5AmMC6/CCC AAA CCT TCG TTC TTG
106534152
8672
60.7






AGT ACA GCA A





 


AJ_P2
85652904
B07
AJ_115
/5AmMC6/CCC AAG AAC ACT CCT
106534153
8666
62.2






CAT GTG ACT GCA A





 


AJ_P2
85652905
B08
AJ_116
/5AmMC6/CCC AAA CGC TTG GTA
106534154
8763
59.3






ACA AAG ACA GTA A





 


AJ_P2
85652906
B09
AJ_117
/5AmMC6/CCC AAC CCT AGA GTA
106534155
8721
58.4






GTA CTA CGG TTA A





 


AJ_P2
85652907
B10
AJ_118
/5AmMC6/CCC AAC CTG AGG TAG
106534156
8779
60.3






TGA CTG AAA CAA A





 


AJ_P2
85652908
B11
AJ_119
/5AmMC6/CCC AAG CTA CGA ACT
106534157
8727
59.7






TGG TTG TTT CAA A





 


AJ_P2
85652909
B12
AJ_120
/5AmMC6/CCC AAG CAA GTC CTA
106534158
8752
60.8






GGT TGT GTT CAA A





 


AJ_P2
85652910
C01
AJ_121
/5AmMC6/CCC AAC TCC ATG TCA
106534159
8755
61.9






AGG AAG GGT ACA A





 


AJ_P2
85652911
C02
AJ_122
/5AmMC6/CCC AAT CCG AAC ACG
106534160
8723
58.7






AAG TAC AAG TTA A





 


AJ_P2
85652912
C03
AJ_123
/5AmMC6/CCC AAC ACG TTG ACA
106534161
8727
60.1






TTG TTG GCT TAA A





 


AJ_P2
85652913
C04
AJ_124
/5AmMC6/CCC AAC CTC TAG GAA
106534162
8675
60.9






CGT AGT ACA CCA A





 


AJ_P2
85652914
C05
AJ_125
/5AmMC6/CCC AAT AGG ACA CCA
106534163
8699
60.3






CAG TTC ATC GAA A





 


AJ_P2
85652915
C06
AJ_126
/5AmMC6/CCC AAA TGT CGT TCG
106534164
8736
59.7






GTT AGC TCA AAA A





 


AJ_P2
85652916
C07
AJ_127
/5AmMC6/CCC AAA TCG GTT GTG
106534165
8736
59.4






TCT AGC TCA AAA A





 


AJ_P2
85652917
C08
AJ_128
/5AmMC6/CCC AAT AAG AAC GAA
106534166
8723
59.3






ACG TAC CTT GCA A





 


AJ_P2
85652918
C09
AJ_129
/5AmMC6/CCC AAT CGC AAG AAC
106534167
8723
59.7






CGT TAG TCA AAA A





 


AJ_P2
85652919
C10
AJ_130
/5AmMC6/CCC AAG TCA CAC GTC
106534168
8657
61.9






TCC ACA GGT TTA A





 


AJ_P2
85652920
C11
AJ_131
/5AmMC6/CCC AAG AGC TTA CAT
106534169
8752
59.4






CGT TCT AGG GTA A





 


AJ_P2
85652921
C12
AJ_132
/5AmMC6/CCC AAG ACC TTC TCC
106534170
8697
61






TTG ACA GAG GTA A





 


AJ_P2
85652922
D01
AJ_133
/5AmMC6/CCC AAA AGG CTT AGC
106534171
8687
58.6






TCT CTT TAC TGA A





 


AJ_P2
85652923
D02
AJ_134
/5AmMC6/CCC AAG TCG TAA CAG
106534172
8755
61.9






AGG TGT CCA CAA A





 


AJ_P2
85652924
D03
AJ_135
/5AmMC6/CCC AAA CTA CTG CAA
106534173
8761
60.5






GTG GTA GGT TCA A





 


AJ_P2
85652925
D04
AJ_136
/5AmMC6/CCC AAT TTC GGA ACC
106534174
8746
62.3






AGT ACC ATG GGA A





 


AJ_P2
85652926
D05
AJ_137
/5AmMC6/CCC AAT CGA GAA GCA
106534175
8705
59.1






ACT TCC TTG TAA A





 


AJ_P2
85652927
D06
AJ_138
/5AmMC6/CCC AAT GGA GAC TTC
106534176
8752
60.3






CGT ACT GTT GAA A





 


AJ_P2
85652928
D07
AJ_139
/5AmMC6/CCC AAA CAT GCG TTT
106534177
8687
59.6






CGT AGT CTT CAA A





 


AJ_P2
85652929
D08
AJ_140
/5AmMC6/CCC AAG AAC CTC AGC
106534178
8690
60.4






TCT TTC GAA AGA A





 


AJ_P2
85652930
D09
AJ_141
/5AmMC6/CCC AAG TCC TTA AGC
106534179
8752
59.7






TGT TCG AGA GTA A





 


AJ_P2
85652931
D10
AJ_142
/5AmMC6/CCC AAT CTC GAA ACT
106534180
8672
60.5






CTT GTG TGA CCA A





 


AJ_P2
85652932
D11
AJ_143
/5AmMC6/CCC AAC CAT TAG AGG
106534181
8763
57.7






AAC TAA GAG CTA A





 


AJ_P2
85652933
D12
AJ_144
/5AmMC6/CCC AAC CCT AGA GTG
106534182
8755
60.7






AGT CAG GAA CTA A





 


AJ_P2
85652934
E01
AJ_145
/5AmMC6/CCC AAT GAA CCA TAA
106534183
8763
59.1






GAG CAA CGG TTA A





 


AJ_P2
85652935
E02
AJ_146
/5AmMC6/CCC AAG AAC CTT CCC
106534184
8672
60.3






TTA GTC GTT GAA A





 


AJ_P2
85652936
E03
AJ_147
/5AmMC6/CCC AAG TGG TCA GTA
106534185
8697
62.1






ACC CTT TCC GAA A





 


AJ_P2
85652937
E04
AJ_148
/5AmMC6/CCC AAA GCA TGT ACG
106534186
8681
59.3






TCT CCT ACT AGA A





 


AJ_P2
85652938
E05
AJ_149
/5AmMC6/CCC AAG GAC TTC ACC
106534187
8666
61.9






TAC GTT CGA ACA A





 


AJ_P2
85652939
E06
AJ_150
/5AmMC6/CCC AAC GAA CTT TAC
106534188
8672
60.7






CTT GTC CAT GGA A





 


AJ_P2
85652940
E07
AJ_151
/5AmMC6/CCC AAC AGG TTC TTA
106534189
8690
61.1






CGC AAC ACA TGA A





 


AJ_P2
85652941
E08
AJ_152
/5AmMC6/CCC AAC TTG TTA GGG
106534190
8752
60.1






TAG CTG ACT CAA A





 


AJ_P2
85652942
E09
AJ_153
/5AmMC6/CCC AAC TGG AGA AGA
106534191
8770
59.2






GAC TAC CTG TTA A





 


AJ_P2
85652943
E10
AJ_154
/5AmMC6/CCC AAC TAA GGT TTG
106534192
8752
60.3






GTC AGT CCT GAA A





 


AJ_P2
85652944
E11
AJ_155
/5AmMC6/CCC AAG CAC ACT AGC
106534193
8690
60.7






CTT TCT GAA AGA A





 


AJ_P2
85652945
E12
AJ_156
/5AmMC6/CCC AAG TCC TGA CGA
106534194
8777
61.6






GAG TTT GGT ACA A





 


AJ_P2
85652946
F01
AJ_157
/5AmMC6/CCC AAT CCC AAG AGT
106534195
8697
61.8






CTC TGG TTG ACA A





 


AJ_P2
85652947
F02
AJ_158
/5AmMC6/CCC AAG GCA TTC AGC
106534196
8687
59.8






ATT CAT TCT TGA A





 


AJ_P2
85652948
F03
AJ_159
/5AmMC6/CCC AAG TTT GAC TAC
106534197
8690
61.3






CAA GCA ACT GCA A





 


AJ_P2
85652949
F04
AJ_160
/5AmMC6/CCC AAC CTT AAG CTA
106534198
8770
60






AGT GTG AGA CGA A





 


AJ_P2
85652950
F05
AJ_161
/5AmMC6/CCC AAC TTA CAG CTA
106534199
8736
59.2






GTT TGA AGT GCA A





 


AJ_P2
85652951
F06
AJ_162
/5AmMC6/CCC AAC TAG TCT CTT
106534200
8727
58.3






AGA GTT TGG CAA A





 


AJ_P2
85652952
F07
AJ_163
/5AmMC6/CCC AAT AAA GCT CTA
106534201
8763
58






GGA GAA CAC GTA A





 


AJ_P2
85652953
F08
AJ_164
/5AmMC6/CCC AAA GCG TAG TAG
106534202
8779
59.8






TGA CTA ACG ACA A





 


AJ_P2
85652954
F09
AJ_165
/5AmMC6/CCC AAG ACG TAA ACG
106534203
8681
59.9






CTT CCT TCT AGA A





 


AJ_P2
85652955
F10
AJ_166
/5AmMC6/CCC AAA GCT GTA GTA
106534204
8672
59.5






CCC TTT CCT AGA A





 


AJ_P2
85652956
F11
AJ_167
/5AmMC6/CCC AAC TCG TAC AGC
106534205
8699
59.3






ATA CCT AGA AGA A





 


AJ_P2
85652957
F12
AJ_168
/5AmMC6/CCC AAT CGC TAC ATA
106534206
8723
58.9






GCA ACT GAA AGA A





 


AJ_P2
85652958
G01
AJ_169
/5AmMC6/CCC AAC TTG GCA ACG
106534207
8761
61






TGT GTA GTA CAA A





 


AJ_P2
85652959
G02
AJ_170
/5AmMC6/CCC AAA CCT GTT ACG
106534208
8696
59.9






CTT GTG CTA AAA A





 


AJ_P2
85652960
G03
AJ_171
/5AmMC6/CCC AAA GCT TGG TTG
106534209
8727
59.4






TAA CTT TAC CGA A





 


AJ_P2
85652961
G04
AJ_172
/5AmMC6/CCC AAG AGA CCT TAG
106534210
8699
60.5






CAA CAA CCT TGA A





 


AJ_P2
85652962
G05
AJ_173
/5AmMC6/CCC AAT ACC GAA GAG
106534211
8761
60.1






TGC TAG GTT TCA A





 


AJ_P2
85652963
G06
AJ_174
/5AmMC6/CCC AAG ACA TAG TAC
106534212
8666
61.6






CGT TGC TAC CCA A





 


AJ_P2
85652964
G07
AJ_175
/5AmMC6/CCC AAG GTC TAG TAA
106534213
8739
59.7






CGA AGC AAC CTA A





 


AJ_P2
85652965
G08
AJ_176
/5AmMC6/CCC AAT AAG CAA CAA
106534214
8723
60.1






AGG TCA TTG CCA A





 


AJ_P2
85652966
G09
AJ_177
/5AmMC6/CCC AAC TGA GTG AGA
106534215
8779
59.5






AGT CAG AAC CTA A





 


AJ_P2
85652967
G10
AJ_178
/5AmMC6/CCC AAC TTC GAG TGA
106534216
8723
58.8






AAC AAG AAC CTA A





 


AJ_P2
85652968
G11
AJ_179
/5AmMC6/CCC AAA GCG TTC ATG
106534217
8727
59.4






GTT CTG TCA TAA A





 


AJ_P2
85652969
G12
AJ_180
/5AmMC6/CCC AAG AGG TCT AGG
106534218
8752
59.7






CTT TCG TCT AAA A





 


AJ_P2
85652970
H01
AJ_181
/5AmMC6/CCC AAA GCC ATT AGT
106534219
8712
60.7






CGT GTC GTT ACA A





 


AJ_P2
85652971
H02
AJ_182
/5AmMC6/CCC AAG GTC TTA CGT
106534220
8777
61.9






AGG TTG AAG CCA A





 


AJ_P2
85652972
H03
AJ_183
/5AmMC6/CCC AAG AGC TTA GCG
106534221
8739
60.2






AAC TTA GAA CCA A





 


AJ_P2
85652973
H04
AJ_184
/5AmMC6/CCC AAT GGA ACC CTA
106534222
8777
61.9






GGG TTG AGT TCA A





 


AJ_P2
85652974
H05
AJ_185
/5AmMC6/CCC AAG AAC ACT TGA
106534223
8730
61






GCA GAC GTT TCA A





 


AJ_P2
85652975
H06
AJ_186
/5AmMC6/CCC AAT CGA AGG AAA
106534224
8763
58.8






GCA TGA CTC TAA A





 


AJ_P2
85652976
H07
AJ_187
/5AmMC6/CCC AAC TTA GTG AGA
106534225
8761
59.3






GTG CTA CTC AGA A





 


AJ_P2
85652977
H08
AJ_188
/5AmMC6/CCC AAA CTT GTT GAA
106534226
8736
59.7






GTG CTT CAC AGA A





 


AJ_P2
85652978
H09
AJ_189
/5AmMC6/CCC AAG TGC TAA CAC
106534227
8672
60.5






TGT TCT CCA TGA A





 


AJ_P2
85652979
H10
AJ_190
/5AmMC6/CCC AAC CCT TAG ACC
106534228
8666
61.7






TGA ACA TCG TGA A





 


AJ_P2
85652980
H11
AJ_191
/5AmMC6/CCC AAC TTA AAG GGT
106534229
8770
59.2






AGA CCT AGT CGA A





 


AJ_P2
85652981
H12
AJ_192
/5AmMC6/CCC AAG GCA TAG ACC
106534230
8712
60.1






TGT CGT TCT TAA A





 


AJ_P3
85652983
A01
AJ_193
/5AmMC6/CCC AAA GCG TTT CTA
106534231
8761
60.1






GGG TAG TAA CCA A





 


AJ_P3
85652984
A02
AJ_194
/5AmMC6/CCC AAG CAA ACT TTC
106534232
8705
59.7






CAA GAC GTT GTA A





 


AJ_P3
85652985
A03
AJ_195
/5AmMC6/CCC AAT CTG GTA ACT
106534233
8672
60.8






GCT TTC GAA CCA A





 


AJ_P3
85652986
A04
AJ_196
/5AmMC6/CCC AAT CAG GAG AGC
106534234
8779
59.4






AAG TAC TAG TCA A





 


AJ_P3
85652987
A05
AJ_197
/5AmMC6/CCC AAA CAT TGT GTC
106534235
8687
59.9






GTT AAC GCT TCA A





 


AJ_P3
85652988
A06
AJ_198
/5AmMC6/CCC AAG AGG TAC TTA
106534236
8770
59.5






GGC ATA ACC GTA A





 


AJ_P3
85652989
A07
AJ_199
/5AmMC6/CCC AAA AAC GGT TTG
106534237
8739
62.2






GCA AAC TGA CCA A





 


AJ_P3
85652990
A08
AJ_200
/5AmMC6/CCC AAC ATA AGG CAA
106534238
8755
62.1






GGG TAC TGT CCA A





 


AJ_P3
85652991
A09
AJ_201
/5AmMC6/CCC AAA TGA CGA CAG
106534239
8795
61.6






GAG TAG TGT CCA A





 


AJ_P3
85652992
A10
AJ_202
/5AmMC6/CCC AAG ACC TTT GCG
106534240
8712
60.4






TTT ACA GGA CTA A





 


AJ_P3
85652993
A11
AJ_203
/5AmMC6/CCC AAG TCT AGA GTC
106534241
8699
59.6






AAC ACA GCA CTA A





 


AJ_P3
85652994
A12
AJ_204
/5AmMC6/CCC AAG AGA GCT TAA
106534242
8715
61.5






CCA GAC TGT CCA A





 


AJ_P3
85652995
B01
AJ_205
/5AmMC6/CCC AAG ACC ATA CTG
106534243
8690
60.1






CAC ATT AGG CTA A





 


AJ_P3
85652996
B02
AJ_206
/5AmMC6/CCC AAG CCA ACT ACG
106534244
8706
61.8






TCA TAG TGG TCA A





 


AJ_P3
85652997
B03
AJ_207
/5AmMC6/CCC AAT GTC GAA CGT
106534245
8699
60.2






ACC AAG ACC ATA A





 


AJ_P3
85652998
B04
AJ_208
/5AmMC6/CCC AAC GTG TAG GAA
106534246
8761
60






GTT CGT ACT CAA A





 


AJ_P3
85652999
B05
AJ_209
/5AmMC6/CCC AAA AAC CGT AAG
106534247
8730
61.3






CCT TCA TGG TGA A





 


AJ_P3
85653000
B06
AJ_210
/5AmMC6/CCC AAT CGG AAA CGC
106534248
8745
59.7






AAG TTC ATG TTA A





 


AJ_P3
85653001
B07
AJ_211
/5AmMC6/CCC AAT CGG TAA CTA
106534249
8763
58.3






GAA AGC ACA GTA A





 


AJ_P3
85653002
B08
AJ_212
/5AmMC6/CCC AAG TCG AAG TAG
106534250
8779
60.1






GCT AAA GTC CAA A





 


AJ_P3
85653003
B09
AJ_213
/5AmMC6/CCC AAA CGG TAG TAC
106534251
8712
59.8






CTT GTC GTC ATA A





 


AJ_P3
85653004
B10
AJ_214
/5AmMC6/CCC AAC ATT TGG AAG
106534252
8727
59.6






TTG CAT CCT GTA A





 


AJ_P3
85653005
B11
AJ_215
/5AmMC6/CCC AAC GAA GTG TTG
106534253
8746
62.6






GTC AAG TCC ACA A





 


AJ_P3
85653006
B12
AJ_216
/5AmMC6/CCC AAT CAA GGA AAG
106534254
8779
60.5






GAC TAG TTC GCA A





 


AJ_P3
85653007
C01
AJ_217
/5AmMC6/CCC AAC GAA ACT TAC
106534255
8723
58.3






AAC GTA GGA CTA A





 


AJ_P3
85653008
C02
AJ_218
/5AmMC6/CCC AAG GCA TGC TTA
106534256
8727
59






GTC TGA ACT TTA A





 


AJ_P3
85653009
C03
AJ_219
/5AmMC6/CCC AAG AAC CGT TCC
106534257
8672
60.5






CAT GTA GCT TTA A





 


AJ_P3
85653010
C04
AJ_220
/5AmMC6/CCC AAG GCA TAA AGT
106534258
8745
59.1






GTT CTC TCG AAA A





 


AJ_P3
85653011
C05
AJ_221
/5AmMC6/CCC AAG GCT ACC CTT
106534259
8739
59.6






AAA GAG GAC ATA A





 


AJ_P3
85653012
C06
AJ_222
/5AmMC6/CCC AAG TCC TAG ACT
106534260
8712
59.8






TCG GTT CGT AAA A





 


AJ_P3
85653013
C07
AJ_223
/5AmMC6/CCC AAG GAA CCT TGT
106534261
8699
60.2






ACA ACA CGA CTA A





 


AJ_P3
85653014
C08
AJ_224
/5AmMC6/CCC AAC ACG TTG TAG
106534262
8779
59.3






AGA CAG AGA CTA A





 


AJ_P3
85653015
C09
AJ_225
/5AmMC6/CCC AAT CCA AGC ACA
106534263
8730
61






AGG TAG GTT TCA A





 


AJ_P3
85653016
C10
AJ_226
/5AmMC6/CCC AAA GCC ATA CTA
106534264
8736
59






GTT GTT GTC GAA A





 


AJ_P3
85653017
C11
AJ_227
/5AmMC6/CCC AAC GAG TAC CAT
106534265
8779
59.2






AGT GAA GGA CTA A





 


AJ_P3
85653018
C12
AJ_228
/5AmMC6/CCC AAC ATT TGC CAA
106534266
8770
60.3






GGG TAG AGA CTA A





 


AJ_P3
85653019
D01
AJ_229
/5AmMC6/CCC AAC GAC TGT TTC
106534267
8687
59.3






CGT AAA GCT TTA A





 


AJ_P3
85653020
D02
AJ_230
/5AmMC6/CCC AAG GAG TAC GAG
106534268
8779
59.7






ACA TCA AGC TTA A





 


AJ_P3
85653021
D03
AJ_231
/5AmMC6/CCC AAT GGA CTG TCT
106534269
8777
61.6






GGA GTA ACG TCA A





 


AJ_P3
85653022
D04
AJ_232
/5AmMC6/CCC AAA CCG TTA CAG
106534270
8752
60.5






GTT TAG TGT CGA A





 


AJ_P3
85653023
D05
AJ_233
/5AmMC6/CCC AAT GAC AAA GAG
106534271
8763
58.6






TAC GAA CTG CTA A





 


AJ_P3
85653024
D06
AJ_234
/5AmMC6/CCC AAT CAC AAG TGA
106534272
8723
59






CAA AGT ACG CTA A





 


AJ_P3
85653025
D07
AJ_235
/5AmMC6/CCC AAC TGT AAA GAG
106534273
8736
58.1






TTG CTA GCT CTA A





 


AJ_P3
85653026
D08
AJ_236
/5AmMC6/CCC AAT GGG AAC ACT
106534274
8795
62.3






GTG AAG TCG ACA A





 


AJ_P3
85653027
D09
AJ_237
/5AmMC6/CCC AAA TTG CGT TTG
106534275
8752
61.9






GTC AAC TGG ACA A





 


AJ_P3
85653028
D10
AJ_238
/5AmMC6/CCC AAC GAA GGT TCA
106534276
8746
62






GGT TAG TCC ACA A





 


AJ_P3
85653029
D11
AJ_239
/5AmMC6/CCC AAA TGC TGT GTT
106534277
8687
59.7






AAC CTT TAG CCA A





 


AJ_P3
85653030
D12
AJ_240
/5AmMC6/CCC AAC CAC TTG TAG
106534278
8712
59.5






TAC TAG GTT CGA A





 


AJ_P3
85653031
E01
AJ_241
/5AmMC6/CCC AAC CCA TAG AGG
106534279
8712
60.3






TTT CAC GTT GTA A





 


AJ_P3
85653032
E02
AJ_242
/5AmMC6/CCC AAC TAG GAA AGA
106534280
8763
58.7






GTT CAA CGC ATA A





 


AJ_P3
85653033
E03
AJ_243
/5AmMC6/CCC AAT CCG AAG AAA
106534281
8779
59.6






GGT CTA CAG GTA A





 


AJ_P3
85653034
E04
AJ_244
/5AmMC6/CCC AAT GGA AAC CCT
106534282
8714
58.9






TAA GAA CTG CTA A





 


AJ_P3
85653035
E05
AJ_245
/5AmMC6/CCC AAG CAA CAT AAC
106534283
8699
60.5






CTT GAC TCA GGA A





 


AJ_P3
85653036
E06
AJ_246
/5AmMC6/CCC AAT AGA ACC ACA
106534284
8723
58.4






GAC TTT AGC AGA A





 


AJ_P3
85653037
E07
AJ_247
/5AmMC6/CCC AAT CAC AAG AGG
106534285
8763
59.1






TTC GTA CGA AAA A





 


AJ_P3
85653038
E08
AJ_248
/5AmMC6/CCC AAA GCT TTG TCT
106534286
8705
59.3






CCA GTA CGA AAA A





 


AJ_P3
85653039
E09
AJ_249
/5AmMC6/CCC AAT CGG AAG GTG
106534287
8770
60.7






TTC AGT AAA CCA A





 


AJ_P3
85653040
E10
AJ_250
/5AmMC6/CCC AAA GTG CAT TCC
106534288
8723
59.4






AAG AAA CGA CTA A





 


AJ_P3
85653041
E11
AJ_251
/5AmMC6/CCC AAG ACG TAA CCA
106534289
8690
60.1






TCG AAC TCG TTA A





 


AJ_P3
85653042
E12
AJ_252
/5AmMC6/CCC AAC CGT AGA ACG
106534290
8687
59.3






TTC TTT GCT TAA A





 


AJ_P3
85653043
F01
AJ_253
/5AmMC6/CCC AAG AGC TCA AGG
106534291
8755
61.6






GTT CTA GAA CCA A





 


AJ_P3
85653044
F02
AJ_254
/5AmMC6/CCC AAT CGG TAG TTA
106534292
8770
60






CGA GTA AAG CCA A





 


AJ_P3
85653045
F03
AJ_255
/5AmMC6/CCC AAG ACA ACT AGC
106534293
8666
61.5






TCT TGG ACT CCA A





 


AJ_P3
85653046
F04
AJ_256
/5AmMC6/CCC AAT GAC GAA GGA
106534294
8739
59.5






CAC TTA GAC CTA A





 


AJ_P3
85653047
F05
AJ_257
/5AmMC6/CCC AAC CGT AGA ACA
106534295
8714
59.1






TTT GAA GCC ATA A





 


AJ_P3
85653048
F06
AJ_258
/5AmMC6/CCC AAC CAC TCG AAC
106534296
8675
62.2






ATG GTA ACG TCA A





 


AJ_P3
85653049
F07
AJ_259
/5AmMC6/CCC AAT CGA ACC GTA
106534297
8690
60.7






ACC ATT TCA GGA A





 


AJ_P3
85653050
F08
AJ_260
/5AmMC6/CCC AAC TAG TGG TTG
106534298
8761
60.5






GAA CAT GCA CTA A





 


AJ_P3
85653051
F09
AJ_261
/5AmMC6/CCC AAG TGC TTA CTG
106534299
8721
60.8






TCC ATC GGA AAA A





 


AJ_P3
85653052
F10
AJ_262
/5AmMC6/CCC AAT GAG TCT GCA
106534300
8687
58.8






TCT CTT TCA AGA A





 


AJ_P3
85653053
F11
AJ_263
/5AmMC6/CCC AAT AGG ACA AAG
106534301
8739
59.8






ACG TCT TAC CGA A





 


AJ_P3
85653054
F12
AJ_264
/5AmMC6/CCC AAT CAT AGG CTA
106534302
8779
59.3






AGG GAA GAC CTA A





 


AJ_P3
85653055
G01
AJ_265
/5AmMC6/CCC AAC AGA GGT AAA
106534303
8795
61.7






GTC CAG TGG TCA A





 


AJ_P3
85653056
G02
AJ_266
/5AmMC6/CCC AAG ACC ACT ACA
106534304
8690
60.7






ACG TTG CAT GTA A





 


AJ_P3
85653057
G03
AJ_267
/5AmMC6/CCC AAT AGA CCA CAA
106534305
8739
60.2






GCA TCG TTA GGA A





 


AJ_P3
85653058
G04
AJ_268
/5AmMC6/CCC AAG TCA CTC ACC
106534306
8681
59.8






TAA GTT CGG TAA A





 


AJ_P3
85653059
G05
AJ_269
/5AmMC6/CCC AAG CTT TCA AGT
106534307
8690
60.3






ACC ACA CGA GTA A





 


AJ_P3
85653060
G06
AJ_270
/5AmMC6/CCC AAG TCA CAT CCT
106534308
8697
61.4






CTA GGG TTC GAA A





 


AJ_P3
85653061
G07
AJ_271
/5AmMC6/CCC AAA AAC GTT CAT
106534309
8736
59.8






TTG GTC TGA CGA A





 


AJ_P3
85653062
G08
AJ_272
/5AmMC6/CCC AAC TGT CCA TTC
106534310
8730
61.2






GGA ACG TGA AAA A





 


AJ_P3
85653063
G09
AJ_273
/5AmMC6/CCC AAA GTT CTT TCT TCA
106534311
8727
59.1






GCA AGG GTA A





 


AJ_P3
85653064
G10
AJ_274
/5AmMC6/CCC AAT AGT CCT GTC
106534312
8712
59.5






GTT AGA ACC GTA A





 


AJ_P3
85653065
G11
AJ_275
/5AmMC6/CCC AAC GTA CAT CCC
106534313
8690
60.2






TTA GAA ACG TGA A





 


AJ_P3
85653066
G12
AJ_276
/5AmMC6/CCC AAC GGT TCA GCA
106534314
8687
59.7






CTT TAC ATT TGA A





 


AJ_P3
85653067
H01
AJ_277
/5AmMC6/CCC AAT GCG TAA ACT
106534315
8672
60.7






CGT TGT CCT ACA A





 


AJ_P3
85653068
H02
AJ_278
/5AmMC6/CCC AAT CGG TAA ACC
106534316
8687
59.4






TGT TTC GCT TAA A





 


AJ_P3
85653069
H03
AJ_279
/5AmMC6/CCC AAG TGC AAG CAC
106534317
8770
61.4






AGG TGA CAT TTA A





 


AJ_P3
85653070
H04
AJ_280
/5AmMC6/CCC AAG GGT ACA GAC
106534318
8795
60.9






GAG TAA CTC TGA A





 


AJ_P3
85653071
H05
AJ_281
/5AmMC6/CCC AAA CCC TAG TAG
106534319
8672
59.1






TTC TAC TCG TGA A





 


AJ_P3
85653072
H06
AJ_282
/5AmMC6/CCC AAG TAA CCC TTC
106534320
8706
61






CGT AGG ACA GTA A





 


AJ_P3
85653073
H07
AJ_283
/5AmMC6/CCC AAT TTA GTC ACT
106534321
8672
60.3






CTG GTC AAC CGA A





 


AJ_P3
85653074
H08
AJ_284
/5AmMC6/CCC AAG TAC ACA ACC
106534322
8715
61.6






TCT GGT AAC GGA A





 


AJ_P3
85653075
H09
AJ_285
/5AmMC6/CCC AAC ACA AGT TCA
106534323
8795
62.2






GGT AGG AGT GCA A





 


AJ_P3
85653076
H10
AJ_286
/5AmMC6/CCC AAC TAA AGG TGT
106534324
8696
59.4






TTA CGC TTC CAA A





 


AJ_P3
85653077
H11
AJ_287
/5AmMC6/CCC AAC TGA AGT TGG
106534325
8777
61.4






TCT ACC TGA GGA A





 


AJ_P3
85653078
H12
AJ_288
/5AmMC6/CCC AAT GTC GTA AGT
106534326
8672
60.8






TCC TCA ACT GCA A





 


AJ_P4
85653080
A01
AJ_289
/5AmMC6/CCC AAA CCT GAG ACC
106534327
8712
60.5






TGT GTT TCG TAA A





 


AJ_P4
85653081
A02
AJ_290
/5AmMC6/CCC AAT AGG CTA GCT
106534328
8723
58.4






CAA CCA TAA AGA A





 


AJ_P4
85653082
A03
AJ_291
/5AmMC6/CCC AAG TTG ACA ACG
106534329
8675
61.8






CTA CCC TAG ACA A





 


AJ_P4
85653083
A04
AJ_292
/5AmMC6/CCC AAT CAC GAA GTG
106534330
8754
59.7






AGC TTG TCA AAA A





 


AJ_P4
85653084
A05
AJ_293
/5AmMC6/CCC AAT GAA ACC GTA
106534331
8690
61.2






ACT CAC TTG GCA A





 


AJ_P4
85653085
A06
AJ_294
/5AmMC6/CCC AAC TTA GCA CAA
106534332
8763
59.2






AGT GTA GAA GCA A





 


AJ_P4
85653086
A07
AJ_295
/5AmMC6/CCC AAT GCG TAG AAC
106534333
8763
59.1






CAT GTA CAA AGA A





 


AJ_P4
85653087
A08
AJ_296
/5AmMC6/CCC AAG AGT TGC TTC
106534334
8761
60.4






GGT ACT CAA AGA A





 


AJ_P4
85653088
A09
AJ_297
/5AmMC6/CCC AAG CGT AGT TCG
106534335
8779
60.3






GAA ACA CTA AGA A





 


AJ_P4
85653089
A10
AJ_298
/5AmMC6/CCC AAA AGA GTC TTA
106534336
8690
59.4






CCG TAC TAC CGA A





 


AJ_P4
85653090
A11
AJ_299
/5AmMC6/CCC AAA AAC GGT AGG
106534337
8706
61.7






TCT CTG ACT CCA A





 


AJ_P4
85653091
A12
AJ_300
/5AmMC6/CCC AAG GTC AGT TAA
106534338
8706
62.4






GCC AAC CCT TGA A





 


AJ_P4
85653092
B01
AJ_301
/5AmMC6/CCC AAA CCA GTC TCT
106534339
8672
60.1






CAG TTT ACG TGA A





 


AJ_P4
85653093
B02
AJ_302
/5AmMC6/CCC AAT AAG ACA AGG
106534340
8699
60.7






ACT TCC ATG CCA A





 


AJ_P4
85653094
B03
AJ_303
/5AmMC6/CCC AAG TCG AGA ACA
106534341
8770
59.9






TGG AAG TCC TTA A





 


AJ_P4
85653095
B04
AJ_304
/5AmMC6/CCC AAT GCA GAG AAA
106534342
8763
58.4






GTA CAT ACC GTA A





 


AJ_P4
85653096
B05
AJ_305
/5AmMC6/CCC AAG TGC ACT TAA
106534343
8779
60.5






GGA CAA CAG GTA A





 


AJ_P4
85653097
B06
AJ_306
/5AmMC6/CCC AAA CCT GTC TTA
106534344
8721
60.2






AGG CAT ACG GTA A





 


AJ_P4
85653098
B07
AJ_307
/5AmMC6/CCC AAG TCT CTA AGT
106534345
8752
59.6






AGG CAT GCT GTA A





 


AJ_P4
85653099
B08
AJ_308
/5AmMC6/CCC AAC GTC TGA CAT
106534346
8770
59.8






TGG AGA GAA CTA A





 


AJ_P4
85653100
B09
AJ_309
/5AmMC6/CCC AAA AAG CTC ACG
106534347
8696
59.3






TCT TGG TCT TAA A





 


AJ_P4
85653101
B10
AJ_310
/5AmMC6/CCC AAG GGT AAC AGA
106534348
8770
60






CAC TTT AGC GTA A





 


AJ_P4
85653102
B11
AJ_311
/5AmMC6/CCC AAT GAC CTA CGA
106534349
8795
60.9






GTG GAG AGT ACA A





 


AJ_P4
85653103
B12
AJ_312
/5AmMC6/CCC AAA GCT TGC GAA
106534350
8723
59.2






ACC TAA CTA AGA A





 


AJ_P4
85653104
C01
AJ_313
/5AmMC6/CCC AAT GTC GAC AGA
106534351
8699
59.6






CCA TAC CTA AGA A





 


AJ_P4
85653105
C02
AJ_314
/5AmMC6/CCC AAG GTC AAC AAG
106534352
8675
62.6






CCA TAC GTT CCA A





 


AJ_P4
85653106
C03
AJ_315
/5AmMC6/CCC AAC TGG TTA CTA
106534353
8770
59.5






CGA ACA GGA GTA A





 


AJ_P4
85653107
C04
AJ_316
/5AmMC6/CCC AAT AGA GAC GTT
106534354
8690
59.1






ACT CCT AAC CGA A





 


AJ_P4
85653108
C05
AJ_317
/5AmMC6/CCC AAA GAC AGT TGA
106534355
8690
60.1






CAC CTT AGC CTA A





 


AJ_P4
85653109
C06
AJ_318
/5AmMC6/CCC AAA TCG AGA GTT
106534356
8690
59.8






ACA CCT TAC CGA A





 


AJ_P4
85653110
C07
AJ_319
/5AmMC6/CCC AAA CAG GTT TCC
106534357
8779
60.4






AAG AAC TAG GGA A





 


AJ_P4
85653111
C08
AJ_320
/5AmMC6/CCC AAG ACA GGT AGG
106534358
8777
61.2






TCT TGC TAG TCA A





 


AJ_P4
85653112
C09
AJ_321
/5AmMC6/CCC AAG GAG TCT CAA
106534359
8715
61.7






CCG TTA ACC AGA A





 


AJ_P4
85653113
C10
AJ_322
/5AmMC6/CCC AAG AAA CGT ACG
106534360
8681
60.7






CTT CTC CAT TGA A





 


AJ_P4
85653114
C11
AJ_323
/5AmMC6/CCC AAC TTA GGA AGC
106534361
8675
61.5






ACT ACG TAC CCA A





 


AJ_P4
85653115
C12
AJ_324
/5AmMC6/CCC AAG TAA GCT ACG
106586457
8657
61.5






TTC CTG TAC CCA A





 


AJ_P4
85653116
D01
AJ_325
/5AmMC6/CCC AAC CAA GTA AGT
106534363
8795
62.1






GGA CAC TGG TGA A





 


AJ_P4
85653117
D02
AJ_326
/5AmMC6/CCC AAC TGT TTA CAG
106534364
8761
60






AGG TCA GCA GTA A





 


AJ_P4
85653118
D03
AJ_327
/5AmMC6/CCC AAC ACG TCT TAA
106534365
8723
58.6






AGC AGA GAA CTA A





 


AJ_P4
85653119
D04
AJ_328
/5AmMC6/CCC AAG AGG ACT GTC
106534366
8697
61.1






CTA CTT CCA TGA A





 


AJ_P4
85653120
D05
AJ_329
/5AmMC6/CCC AAG AAC ATC TCC
106534367
8666
61.6






ACT GGT CAC GTA A





 


AJ_P4
85653121
D06
AJ_330
/5AmMC6/CCC AAT GAA GCA ACA
106534368
8739
60.9






AGT GGT ACT CCA A





 


AJ_P4
85653122
D07
AJ_331
/5AmMC6/CCC AAT CCG TAA CAG
106534369
8779
59.5






TAG GAG AAC GTA A





 


AJ_P4
85653123
D08
AJ_332
/5AmMC6/CCC AAA CCG TAG GAA
106534370
8690
60






CTA CCA TTC TGA A





 


AJ_P4
85653124
D09
AJ_333
/5AmMC6/CCC AAC CAG TTC GTT
106534371
8690
60.8






CAA ACA GAC TGA A





 


AJ_P4
85653125
D10
AJ_334
/5AmMC6/CCC AAG TTA AAC ATC
106534372
8699
60.4






CAG AGC TCA CGA A





 


AJ_P4
85653126
D11
AJ_335
/5AmMC6/CCC AAG TCA CAC AAC
106534373
8715
61.9






CTA GAG CTT GGA A





 


AJ_P4
85653127
D12
AJ_336
/5AmMC6/CCC AAC ATG TTA GGG
106534374
8752
61






TTA CCT TGG CAA A





 


AJ_P4
85653128
E01
AJ_337
/5AmMC6/CCC AAG TCA AAG GTA
106534375
8666
61.7






CTC CAC TTC CGA A





 


AJ_P4
85653129
E02
AJ_338
/5AmMC6/CCC AAG TAG AAC GTC
106534376
8699
60






AAC CAC TTA CGA A





 


AJ_P4
85653130
E03
AJ_339
/5AmMC6/CCC AAG GAG ACT TGT
106534377
8697
60.5






CCT ACT CTA CGA A





 


AJ_P4
85653131
E04
AJ_340
/5AmMC6/CCC AAT TTC GTA GTA
106534378
8687
58.9






CTC ACT TGC GAA A





 


AJ_P4
85653132
E05
AJ_341
/5AmMC6/CCC AAC CTT GTA CTA
106534379
8770
59.5






GGA AGG AAG CTA A





 


AJ_P4
85653133
E06
AJ_342
/5AmMC6/CCC AAG TCG TAG TTG
106534380
8697
62.3






TCA CAC TGC ACA A





 


AJ_P4
85653134
E07
AJ_343
/5AmMC6/CCC AAC GAA GTT ACG
106534381
8672
61






TCT TTC ATG CCA A





 


AJ_P4
85653135
E08
AJ_344
/5AmMC6/CCC AAA AGG CAT AAG
106534382
8730
61.3






GCT TGT CAT CCA A





 


AJ_P4
85653136
E09
AJ_345
/5AmMC6/CCC AAG TGT CCA TAC
106534383
8681
60.8






GCT TTA CCG AAA A





 


AJ_P4
85653137
E10
AJ_346
/5AmMC6/CCC AAC GGT TGA CAC
106534384
8715
62.3






CAG TTA CCA AGA A





 


AJ_P4
85653138
E11
AJ_347
/5AmMC6/CCC AAG TGT GCA ACC
106534385
8697
62.2






AGT TAC TCC TGA A





 


AJ_P4
85653139
E12
AJ_348
/5AmMC6/CCC AAG CTG ACA GAC
106534386
8672
60.1






TCT CTT TCA TGA A





 


AJ_P4
85653140
F01
AJ_349
/5AmMC6/CCC AAG AAA GCT GTA
106534387
8681
59.4






CCC TTC TCT AGA A





 


AJ_P4
85653141
F02
AJ_350
/5AmMC6/CCC AAA TGT TGC TAC
106534388
8714
59






AAG ACT AAC CGA A





 


AJ_P4
85653142
F03
AJ_351
/5AmMC6/CCC AAG TCT GGA AGT
106534389
8777
61.4






GCT AGT ACG TCA A





 


AJ_P4
85653143
F04
AJ_352
/5AmMC6/CCC AAT CGC AAC TTC
106534390
8687
59.4






GGT ACA TTT GTA A





 


AJ_P4
85653144
F05
AJ_353
/5AmMC6/CCC AAC CTG TAA CAT
106534391
8754
59






TGA AGA AGC GTA A





 


AJ_P4
85653145
F06
AJ_354
/5AmMC6/CCC AAA CTG TTG GAA
106534392
8754
59.4






AGC TGA ACA CTA A





 


AJ_P4
85653146
F07
AJ_355
/5AmMC6/CCC AAG ACG TAG CTT
106534393
8779
58.9






AGA GAG AAC CTA A





 


AJ_P4
85653147
F08
AJ_356
/5AmMC6/CCC AAC ATT GTT GTG
106534394
8761
60.7






GAA CCT CAG AGA A





 


AJ_P4
85653148
F09
AJ_357
/5AmMC6/CCC AAG TGG ACT AGC
106534395
8697
61.2






TTC CTA CAC TGA A





 


AJ_P4
85653149
F10
AJ_358
/5AmMC6/CCC AAA GGA ACT GAC
106534396
8723
59.2






ATT CAA CAC GTA A





 


AJ_P4
85653150
F11
AJ_359
/5AmMC6/CCC AAT GTT CGA GTC
106534397
8690
60.2






CAC AAC TAC AGA A





 


AJ_P4
85653151
F12
AJ_360
/5AmMC6/CCC AAG TAA CTA CTC
106534398
8739
59






ACA GAG CTA GGA A





 


AJ_P4
85653152
G01
AJ_361
/5AmMC6/CCC AAG AGG ACT CAC
106534399
8706
61.2






CAG TAC TTT CGA A





 


AJ_P4
85653153
G02
AJ_362
/5AmMC6/CCC AAT AGC GTT GTT TCT
106534400
8687
59






AAC CAC TGA A





 


AJ_P4
85653154
G03
AJ_363
/5AmMC6/CCC AAC ATT TGT TAG
106534401
8736
59






TAG CAG TCA CGA A





 


AJ_P4
85653155
G04
AJ_364
/5AmMC6/CCC AAT AAC AGC AAG
106534402
8699
60.8






ACC TTG TAG CCA A





 


AJ_P4
85653156
G05
AJ_365
/5AmMC6/CCC AAG ACT CTC CAC
106534403
8675
61.9






ACG TTG AAG ACA A





 


AJ_P4
85653157
G06
AJ_366
/5AmMC6/CCC AAG AAC TCC ATC
106534404
8666
61.7






CTG TTC GAC AGA A





 


AJ_P4
85653158
G07
AJ_367
/5AmMC6/CCC AAG GTT CTA GTT
106534405
8681
60.4






CCA ACT AAC GCA A





 


AJ_P4
85653159
G08
AJ_368
/5AmMC6/CCC AAA GTT GCG TTT
106534406
8727
59






GTC ATA GAC CTA A





 


AJ_P4
85653160
G09
AJ_369
/5AmMC6/CCC AAC GCT TGA GGT
106534407
8763
59






AAA CTA AAC AGA A





 


AJ_P4
85653161
G10
AJ_370
/5AmMC6/CCC AAT AAC GAG TAG
106534408
8739
59






AGC TCT AGA CCA A





 


AJ_P4
85653162
G11
AJ_371
/5AmMC6/CCC AAG TGA GTC ATA
106534409
8739
60.5






GCC ATA AGC CAA A





 


AJ_P4
85653163
G12
AJ_372
/5AmMC6/CCC AAC TTA CGT GAC
106534410
8672
60.3






TTC CAT TCA GGA A





 


AJ_P4
85653164
H01
AJ_373
/5AmMC6/CCC AAA TCA GTG ACT
106534411
8672
60.1






GTC TCT TCA CGA A





 


AJ_P4
85653165
H02
AJ_374
/5AmMC6/CCC AAA GGT ACT GAC
106534412
8657
61.4






TTC CAC TCC TGA A





 


AJ_P4
85653166
H03
AJ_375
/5AmMC6/CCC AAT CGA CAT TAC
106534413
8779
59.9






AGG AAG TAC GGA A





 


AJ_P4
85653167
H04
AJ_376
/5AmMC6/CCC AAC CAC TGG TTA
106534414
8739
60.9






AAC GTA AAC GGA A





 


AJ_P4
85653168
H05
AJ_377
/5AmMC6/CCC AAG TTC ATT CCC
106534415
8672
60.7






TAA GCC TTG GAA A





 


AJ_P4
85653169
H06
AJ_378
/5AmMC6/CCC AAG AAA CTA CTC
106534416
8730
60.1






CAT GGT TAG CGA A





 


AJ_P4
85653170
H07
AJ_379
/5AmMC6/CCC AAC TAA GGG TTA
106534417
8745
58.4






AAG CTT ACC GTA A





 


AJ_P4
85653171
H08
AJ_380
/5AmMC6/CCC AAG AGA CCT GTC
106534418
8690
60.1






ACA CTT TAA CGA A





 


AJ_P4
85653172
H09
AJ_381
/5AmMC6/CCC AAT GAA CAA CAA
106534419
8723
59.8






CAT GCT TAC GGA A





 


AJ_P4
85653173
H10
AJ_382
/5AmMC6/CCC AAT CAG AAA GCA
106534420
8763
58.9






ACA TTC TAG GGA A





 


AJ_P4
85653174
H11
AJ_383
/5AmMC6/CCC AAT AGG CTT GAC
106534421
8705
58.8






TCA TTA AAC CGA A





 


AJ_P4
85653175
H12
AJ_384
/5AmMC6/CCC AAA CTG GTT TGT
106534422
8712
60.3






AGT CCT ACC GAA A





 


AJ_P5
85653177
A01
AJ_385
/5AmMC6/CCC AAA CCT GAC AGC
106534423
8687
59






TTG TTT CTT AGA A





 


AJ_P5
85653178
A02
AJ_386
/5AmMC6/CCC AAC TTG CTA CAT
106534424
8770
59.9






AGA GAG AGT GCA A





 


AJ_P5
85653179
A03
AJ_387
/5AmMC6/CCC AAG GTA AAC CTT
106534425
8666
61.5






CCA GTC TCC AGA A





 


AJ_P5
85653180
A04
AJ_388
/5AmMC6/CCC AAT ACC AAG TAC
106534426
8739
60.8






GCA AAC TGT GGA A





 


AJ_P5
85653181
A05
AJ_389
/5AmMC6/CCC AAC CGT AAA CCT
106534427
8730
60.5






TAA GGT GTA GCA A





 


AJ_P5
85653182
A06
AJ_390
/5AmMC6/CCC AAC ATT GTT TCC
106534428
8681
61.6






CAA GGC ATA GCA A





 


AJ_P5
85653183
A07
AJ_391
/5AmMC6/CCC AAG GTC ATC CTA
106534429
8657
61.9






CTA GCA TTG CCA A





 


AJ_P5
85653184
A08
AJ_392
/5AmMC6/CCC AAG TTC AAC ATC
106534430
8681
60.4






ACT GCT ACG GTA A





 


AJ_P5
85653185
A09
AJ_393
/5AmMC6/CCC AAT TCG CAT GCA
106534431
8727
60.1






TTT AAG GTG TCA A





 


AJ_P5
85653186
A10
AJ_394
/5AmMC6/CCC AAC TTA GCA CTA
106534432
8779
59.4






GAG AAG GAG TCA A





 


AJ_P5
85653187
A11
AJ_395
/5AmMC6/CCC AAG CTC AGG ACA
106534433
8777
62.2






GTT GAG TGT TCA A





 


AJ_P5
85653188
A12
AJ_396
/5AmMC6/CCC AAG TCC TAG CTA
106534434
8761
59.7






AGA GTG TGT CAA A





 


AJ_P5
85653189
B01
AJ_397
/5AmMC6/CCC AAG CTA CAA GCA
106534435
8754
59.3






TAA GTG GTT CAA A





 


AJ_P5
85653190
B02
AJ_398
/5AmMC6/CCC AAG TCA TAC CAA
106534436
8739
60






AGC TGA GAC GTA A





 


AJ_P5
85653191
B03
AJ_399
/5AmMC6/CCC AAT TTA GCA TAG
106534437
8754
58






ACG AGA GAC TCA A





 


AJ_P5
85653192
B04
AJ_400
/5AmMC6/CCC AAT TTC ATG TAA
106534438
8745
59.4






CGA CAG TGA GCA A





 


AJ_P5
85653193
B05
AJ_401
/5AmMC6/CCC AAT GCA CTT CGT
106534439
8754
58.6






AGA GTA AGA ACA A





 


AJ_P5
85653194
B06
AJ_402
/5AmMC6/CCC AAA CGT TGT CTC
106534440
8752
60.5






TGT AGT GGA ACA A





 


AJ_P5
85653195
B07
AJ_403
/5AmMC6/CCC AAC CGA AGT TAG
106534441
8699
60.8






CAA ACC TCA TGA A





 


AJ_P5
85653196
B08
AJ_404
/5AmMC6/CCC AAC ATT TAG AAG
106534442
8754
58.8






GAC TTC GAA CGA A





 


AJ_P5
85653197
B09
AJ_405
/5AmMC6/CCC AAG TTC CAA CAC
106534443
8675
62






TCA GAC AGG TCA A





 


AJ_P5
85653198
B10
AJ_406
/5AmMC6/CCC AAT GAC AAC CTC
106534444
8706
61.7






TCA GAG TGG TCA A





 


AJ_P5
85653199
B11
AJ_407
/5AmMC6/CCC AAG CCT AGG TAG
106534445
8777
61






GTT CTG GAA CTA A





 


AJ_P5
85653200
B12
AJ_408
/5AmMC6/CCC AAT CGA ACA CAC
106534446
8690
60.6






CAT GTT ACT GGA A





 


AJ_P5
85653201
C01
AJ_409
/5AmMC6/CCC AAT AGT CTA ACT
106534447
8727
59.3






GTT GGC TTG CAA A





 


AJ_P5
85653202
C02
AJ_410
/5AmMC6/CCC AAA AGC TAG GTA
106534448
8681
59.8






CCT TCT TAC CGA A





 


AJ_P5
85653203
C03
AJ_411
/5AmMC6/CCC AAC TCA GAG TAC
106534449
8770
60






AGA GAG TTT GCA A





 


AJ_P5
85653204
C04
AJ_412
/5AmMC6/CCC AAG ACA CGT CAT
106534450
8795
61.4






AGG AGT GTA GCA A





 


AJ_P5
85653205
C05
AJ_413
/5AmMC6/CCC AAT TAA GCA TAA
106534451
8763
59.2






CGA GAC AGT GCA A





 


AJ_P5
85653206
C06
AJ_414
/5AmMC6/CCC AAG TGT CCA CAT
106534452
8795
62.6






GAG GTG AAA GCA A





 


AJ_P5
85653207
C07
AJ_415
/5AmMC6/CCC AAC TAA AGG GTT
106534453
8770
60.6






GAA CGT TCC AGA A





 


AJ_P5
85653208
C08
AJ_416
/5AmMC6/CCC AAA TCG CTT TCT TTA
106534454
8727
59.1






GTG GAG ACA A





 


AJ_P5
85653209
C09
AJ_417
/5AmMC6/CCC AAA GGT CTT CAC
106534455
8696
60.1






TTT GTG CAC AAA A





 


AJ_P5
85653210
C10
AJ_418
/5AmMC6/CCC AAG GCT TAA GGT
106534456
8755
62.3






GAA CCA TCG ACA A





 


AJ_P5
85653211
C11
AJ_419
/5AmMC6/CCC AAC TGT AGA GCT
106534457
8699
59.3






ACC AAC ACT AGA A





 


AJ_P5
85653212
C12
AJ_420
/5AmMC6/CCC AAC TAA GGG TTG
106534458
8752
60.5






TTA CGT TAG CCA A





 


AJ_P5
85653213
D01
AJ_421
/5AmMC6/CCC AAG TGG TAC TCA
106534459
8697
61.4






GCT ACA TCG TCA A





 


AJ_P5
85653214
D02
AJ_422
/5AmMC6/CCC AAG TCC AAA CAC
106534460
8675
62.3






CTT GAG AGC TCA A





 


AJ_P5
85653215
D03
AJ_423
/5AmMC6/CCC AAT CAC AAG CTT
106534461
8779
60.1






AGA GTG GAG ACA A





 


AJ_P5
85653216
D04
AJ_424
/5AmMC6/CCC AAC TTT GAC TTT
106534462
8752
60.9






GGC AAC TAG GGA A





 


AJ_P5
85653217
D05
AJ_425
/5AmMC6/CCC AAC CTC AGT CTA
106534463
8737
61






AGG GTA GTG TCA A





 


AJ_P5
85653218
D06
AJ_426
/5AmMC6/CCC AAA CAC CTG TCC
106534464
8715
61.6






AGA GAG TGT ACA A





 


AJ_P5
85653219
D07
AJ_427
/5AmMC6/CCC AAC ATA GTT GTG
106534465
8745
59.2






AAG CAT CGC TAA A





 


AJ_P5
85653220
D08
AJ_428
/5AmMC6/CCC AAA CGT GTT GTT
106534466
8752
60.6






GTA CCC TAG GAA A





 


AJ_P5
85653221
D09
AJ_429
/5AmMC6/CCC AAA CTT TGG TAG
106534467
8754
59.4






AAA CGT AGC CAA A





 


AJ_P5
85653222
D10
AJ_430
/5AmMC6/CCC AAC TCA GTT GCA
106534468
8736
59.9






TTA AAG TGT GCA A





 


AJ_P5
85653223
D11
AJ_431
/5AmMC6/CCC AAA CTA CTG TTC
106534469
8712
60.2






TGG ACT TCG GAA A





 


AJ_P5
85653224
D12
AJ_432
/5AmMC6/CCC AAA GAG CAT TAG
106534470
8779
60






GAC TGT ACG ACA A





 


AJ_P5
85653225
E01
AJ_433
/5AmMC6/CCC AAC ACC ATG CTG
106534471
8746
62.3






AGT GGT AAG TCA A





 


AJ_P5
85653226
E02
AJ_434
/5AmMC6/CCC AAC TGG AAC ACG
106534472
8795
62.2






TGT GGT AGA ACA A





 


AJ_P5
85653227
E03
AJ_435
/5AmMC6/CCC AAC CTC AGA ACT
106534473
8657
62






CGT TGG TTA CCA A





 


AJ_P5
85653228
E04
AJ_436
/5AmMC6/CCC AAT GCC ATA ACG
106534474
8687
59.3






CTT GTA CTT GTA A





 


AJ_P5
85653229
E05
AJ_437
/5AmMC6/CCC AAA ACC TTG TAG
106534475
8763
59






ACA AGA AGC GTA A





 


AJ_P5
85653230
E06
AJ_438
/5AmMC6/CCC AAC ACA TGT TAG
106534476
8779
59.8






AGA CGA CAG GTA A





 


AJ_P5
85653231
E07
AJ_439
/5AmMC6/CCC AAG GTA CTC TAA
106534477
8672
59.4






CTT GCA GTC CTA A





 


AJ_P5
85653232
E08
AJ_440
/5AmMC6/CCC AAT GCC AAC CTC
106534478
8699
60.9






AAG AAG TGT ACA A





 


AJ_P5
85653233
E09
AJ_441
/5AmMC6/CCC AAC TAA AGT TGG
106534479
8739
61.2






GAA CGC ATC ACA A





 


AJ_P5
85653234
E10
AJ_442
/5AmMC6/CCC AAG GAC TAC TCC
106534480
8666
61






ACT GTC ATC AGA A





 


AJ_P5
85653235
E11
AJ_443
/5AmMC6/CCC AAG AAC CGT AGT
106534481
8657
61






TCC TTC CCT AGA A





 


AJ_P5
85653236
E12
AJ_444
/5AmMC6/CCC AAC TTT GAG GTG
106534482
8752
60.1






AGA CTC GTT ACA A





 


AJ_P5
85653237
F01
AJ_445
/5AmMC6/CCC AAT CAG AGA AGA
106534483
8739
60.1






GTT CGT CAC ACA A





 


AJ_P5
85653238
F02
AJ_446
/5AmMC6/CCC AAG TTT CAT TCC TCA
106534484
8672
60.5






GAG CTG ACA A





 


AJ_P5
85653239
F03
AJ_447
/5AmMC6/CCC AAG TTG TCA CTC
106534485
8657
61.8






CTG AGC ACT ACA A





 


AJ_P5
85653240
F04
AJ_448
/5AmMC6/CCC AAA AGG TTC ATC
106534486
8681
61.5






GCT TTG ACC ACA A





 


AJ_P5
85653241
F05
AJ_449
/5AmMC6/CCC AAT GCC AAG ACT
106534487
8752
61.2






TGT GGT GTT ACA A





 


AJ_P5
85653242
F06
AJ_450
/5AmMC6/CCC AAA GGC TTC GGT
106534488
8739
60.4






AAC ACT AAC AGA A





 


AJ_P5
85653243
F07
AJ_451
/5AmMC6/CCC AAC AGC TAG CAT
106534489
8752
61.1






GGT TTG GTT ACA A





 


AJ_P5
85653244
F08
AJ_452
/5AmMC6/CCC AAG CCA TTA GCC
106534490
8657
62.2






TAG TTG TCC ACA A





 


AJ_P5
85653245
F09
AJ_453
/5AmMC6/CCC AAC GGT ACA ACG
106534491
8777
62.7






GTT GGG TTT ACA A





 


AJ_P5
85653246
F10
AJ_454
/5AmMC6/CCC AAC ACC AGT TGG
106534492
8715
62.5






ACA GGA CAT TCA A





 


AJ_P5
85653247
F11
AJ_455
/5AmMC6/CCC AAT CTC AGA CTG
106534493
8786
61.8






GAA GGG TTG ACA A





 


AJ_P5
85653248
F12
AJ_456
/5AmMC6/CCC AAG TGT GAC GAA
106534494
8739
60.9






CCT CAA ACA TGA A





 


AJ_P5
85653249
G01
AJ_457
/5AmMC6/CCC AAT GCG TAC AGG
106534495
8779
60.1






TAC ATA GGA CAA A





 


AJ_P5
85653250
G02
AJ_458
/5AmMC6/CCC AAC AGT TAA AGG
106534496
8763
59.1






ACA TGA GCT CAA A





 


AJ_P5
85653251
G03
AJ_459
/5AmMC6/CCC AAT CCG AAA GGG
106534497
8770
60.3






TTA CAG TTA CGA A





 


AJ_P5
85653252
G04
AJ_460
/5AmMC6/CCC AAC ATT GTG AAA
106534498
8721
61.6






GTG CAG TTC CCA A





 


AJ_P5
85653253
G05
AJ_461
/5AmMC6/CCC AAA ACC ATG AGG
106534499
8675
62.5






TCA CGT TAC CCA A





 


AJ_P5
85653254
G06
AJ_462
/5AmMC6/CCC AAT CAA GGA GAA
106534500
8739
60.3






ACG TGT ACC TCA A





 


AJ_P5
85653255
G07
AJ_463
/5AmMC6/CCC AAT CAG GAG ACG
106534501
8795
60.6






ACT AGT AGG TCA A





 


AJ_P5
85653256
G08
AJ_464
/5AmMC6/CCC AAG GAC TAG GTC
106534502
8706
61






ACA CAT CTC TGA A





 


AJ_P5
85653257
G09
AJ_465
/5AmMC6/CCC AAC ATA GAG AGG
106534503
8739
59.5






ACA TCT TCG ACA A





 


AJ_P5
85653258
G10
AJ_466
/5AmMC6/CCC AAC GAA CTC ATC
106534504
8666
62.3






CTT GTG GAC ACA A





 


AJ_P5
85653259
G11
AJ_467
/5AmMC6/CCC AAC AGT TGG TGA
106534505
8761
61.5






GTT CAT GCA CAA A





 


AJ_P5
85653260
G12
AJ_468
/5AmMC6/CCC AAC ATA GGA CAG
106534506
8795
62.3






GAG TGT TGC ACA A





 


AJ_P5
85653261
H01
AJ_469
/5AmMC6/CCC AAC TAG TAG AAG
106534507
8779
59.8






ACT GCA TGG ACA A





 


AJ_P5
85653262
H02
AJ_470
/5AmMC6/CCC AAT AGA GCA AGA
106534508
8779
60.2






ACC TCA GTT GGA A





 


AJ_P5
85653263
H03
AJ_471
/5AmMC6/CCC AAC CAT GTG GAG
106534509
8777
62.1






TTT CTG AGG ACA A





 


AJ_P5
85653264
H04
AJ_472
/5AmMC6/CCC AAT AGA CAG GAC
106534510
8755
61.9






AGG TGT TCC CAA A





 


AJ_P5
85653265
H05
AJ_473
/5AmMC6/CCC AAT TCG GAA GCC
106534511
8687
58.8






ATT TCT CTT AGA A





 


AJ_P5
85653266
H06
AJ_474
/5AmMC6/CCC AAT CGG AAC AGT
106534512
8672
60.3






TCC TCA TTC TGA A





 


AJ_P5
85653267
H07
AJ_475
/5AmMC6/CCC AAT GAA GCA GTT
106534513
8696
59.2






CCA TCA TTC TGA A





 


AJ_P5
85653268
H08
AJ_476
/5AmMC6/CCC AAC ATG TGT CAA
106534514
8737
61.9






GGG TAG CTC TCA A





 


AJ_P5
85653269
H09
AJ_477
/5AmMC6/CCC AAG CCT TTA CAC
106534515
8666
62.8






CAT GTG GAA CCA A





 


AJ_P5
85653270
H10
AJ_478
/5AmMC6/CCC AAC TAA CTG CTG
106534516
8786
61.5






AGG TGA GGT ACA A





 


AJ_P5
85653271
H11
AJ_479
/5AmMC6/CCC AAC TCC AAG TCG
106534517
8746
61.9






AGT GAG TTG ACA A





 


AJ_P5
85653272
H12
AJ_480
/5AmMC6/CCC AAC GAG TTG AGA
106534518
8779
60.3






AGC TAC ATG ACA A





 


AJ_P6
85653274
A01
AJ_481
/5AmMC6/CCC AAT TTC TGA GTG
106534519
8721
60.2






AGC AAC CCT AGA A





 


AJ_P6
85653275
A02
AJ_482
/5AmMC6/CCC AAG AGT ACA GCT
106534520
8675
60.8






ACC TCT CCA AGA A





 


AJ_P6
85653276
A03
AJ_483
/5AmMC6/CCC AAG AGC ACT CCA
106534521
8699
60.4






CTT GTA CAA AGA A





 


AJ_P6
85653277
A04
AJ_484
/5AmMC6/CCC AAG CTA CAT TTC
106534522
8687
58.3






TTG AGT CGA CTA A





 


AJ_P6
85653278
A05
AJ_485
/5AmMC6/CCC AAA CCG TAG GAC
106534523
8699
60.2






TAC AAC ACT TGA A





 


AJ_P6
85653279
A06
AJ_486
/5AmMC6/CCC AAA TTC CTG TTG
106534524
8752
60.8






TGA CGA AGT CGA A





 


AJ_P6
85653280
A07
AJ_487
/5AmMC6/CCC AAA GTT CTG TGG
106534525
8752
60.8






TTC ACA AGT CGA A





 


AJ_P6
85653281
A08
AJ_488
/5AmMC6/CCC AAG TAC TCG AGT
106534526
8672
59.8






TCC CTT TAA CGA A





 


AJ_P6
85653282
A09
AJ_489
/5AmMC6/CCC AAG CTG AAG GTT
106534527
8763
59.3






AAC AAC AAG CTA A





 


AJ_P6
85653283
A10
AJ_490
/5AmMC6/CCC AAT CGC ATG GTA
106534528
8723
59.8






AAC AAA CAC TGA A





 


AJ_P6
85653284
A11
AJ_491
/5AmMC6/CCC AAC TGG TAC TAA
106534529
8699
61






AGC CAA ACT GCA A





 


AJ_P6
85653285
A12
AJ_492
/5AmMC6/CCC AAC GTT AAG AAG
106534530
8730
59.4






GTA CCT AGC CTA A





 


AJ_P6
85653286
B01
AJ_493
/5AmMC6/CCC AAC AGT GAA AGT
106534531
8721
60.6






TGT CCT TCC AGA A





 


AJ_P6
85653287
B02
AJ_494
/5AmMC6/CCC AAC AGG AGT TGG
106534532
8786
61.4






GTA CCA GTC TAA A





 


AJ_P6
85653288
B03
AJ_495
/5AmMC6/CCC AAG AAA CTG TGC
106534533
8699
61.1






AAA CAC TCC TGA A





 


AJ_P6
85653289
B04
AJ_496
/5AmMC6/CCC AAT CGT AGT TCG
106534534
8690
60.1






ACA AAC TCC AGA A





 


AJ_P6
85653290
B05
AJ_497
/5AmMC6/CCC AAC AGG TTA GTT
106534535
8666
62.1






CAC ACC ATC CGA A





 


AJ_P6
85653291
B06
AJ_498
/5AmMC6/CCC AAG GTT TAC GTC
106534536
8657
61.7






ACT CCA TCC AGA A





 


AJ_P6
85653292
B07
AJ_499
/5AmMC6/CCC AAG TTT AAC CTC
106534537
8687
59.3






ATG CTT TAG CGA A





 


AJ_P6
85653293
B08
AJ_500
/5AmMC6/CCC AAT TTG TAC GTT
106534538
8672
60.9






CCA ACC TAG GCA A





 


AJ_P6
85653294
B09
AJ_501
/5AmMC6/CCC AAA TCG TTT GTT TCC
106534539
8727
59.8






AGT AGG CAA A





 


AJ_P6
85653295
B10
AJ_502
/5AmMC6/CCC AAG CAT CCT TGT CTT
106586458
8672
60.7






AAC TGC AGA A





 


AJ_P6
85653296
B11
AJ_503
/5AmMC6/CCC AAA CTG GTA AGT
106534541
8697
62






CTT GGC TAC CCA A





 


AJ_P6
85653297
B12
AJ_504
/5AmMC6/CCC AAG TCC ATG TGC
106534542
8675
63






AAC ACC AAC TGA A





 


AJ_P6
85653298
C01
AJ_505
/5AmMC6/CCC AAG TCA CAG GAC
106534543
8675
61.7






TCC TCA ACA TGA A





 


AJ_P6
85653299
C02
AJ_506
/5AmMC6/CCC AAG TAC TCT CAT TCT
106577185
8672
60.1






GTG CAG ACA A





 


AJ_P6
85653300
C03
AJ_507
/5AmMC6/CCC AAG GTT CCA CAC
106577186
8657
62.6






TTT GTC ACG ACA A





 


AJ_P6
85653301
C04
AJ_508
/5AmMC6/CCC AAA CTC GTC TGT
106586459
8681
60.1






CCA TAA AGT CGA A





 


AJ_P6
85653302
C05
AJ_509
/5AmMC6/CCC AAC AAG GTG TGT
106577187
8712
60.6






TCT ACC ATT CGA A





 


AJ_P6
85653303
C06
AJ_510
/5AmMC6/CCC AAA CTC GTG TTG
106577188
8736
58.6






TAC TTA GAA CGA A





 


AJ_P6
85653304
C07
AJ_511
/5AmMC6/CCC AAA GGC ATT GTC
106534549
8723
59.9






AAC AAA CCA GTA A





 


AJ_P6
85653305
C08
AJ_512
/5AmMC6/CCC AAC AGT AGT TGT
106577189
8736
58.5






TAA CGA CTG CTA A





 


AJ_P6
85653306
C09
AJ_513
/5AmMC6/CCC AAT GCT CAG GTC
106534551
8723
59.1






AAA CAA ACT AGA A





 


AJ_P6
85653307
C10
AJ_514
/5AmMC6/CCC AAT GTC GTA CTT
106586460
8727
58.3






TGA GTA AGC CTA A





 


AJ_P6
85653308
C11
AJ_515
/5AmMC6/CCC AAG GCT AGA CGA
106534553
8739
60.2






ACA TTA CCA TGA A





 


AJ_P6
85653309
C12
AJ_516
/5AmMC6/CCC AAC GAG TGT TCT
106586461
8752
60






AGT GTT ACA CGA A





 


AJ_P6
85653310
D01
AJ_517
/5AmMC6/CCC AAC AGG TTT ACG
106534555
8752
60.3






TGT GTA CAG CTA A





 


AJ_P6
85653311
D02
AJ_518
/5AmMC6/CCC AAA GGT TCC TTC
106534556
8672
60.6






CAT GTA AGC TCA A





 


AJ_P6
85653312
D03
AJ_519
/5AmMC6/CCC AAA GGC TTT GCT
106534557
8727
59.3






GTT ACT TAG ACA A





 


AJ_P6
85653313
D04
AJ_520
/5AmMC6/CCC AAC AAA GTA ACT
106534558
8745
59.9






GTT CGT TGC GAA A





 


AJ_P6
85653314
D05
AJ_521
/5AmMC6/CCC AAA TGC TTG GAA
106534559
8696
59.1






CTT CTA ACT CGA A





 


AJ_P6
85653315
D06
AJ_522
/5AmMC6/CCC AAC CTG AGT ACT
106534560
8721
60.4






GTG CTC TGA AAA A





 


AJ_P6
85653316
D07
AJ_523
/5AmMC6/CCC AAG GAC TCA AGT
106534561
8657
61.6






CTT CCT TCA CGA A





 


AJ_P6
85653317
D08
AJ_524
/5AmMC6/CCC AAA GGG TTC CGT
106534562
8721
60.7






TCA CTA ACA TGA A





 


AJ_P6
85653318
D09
AJ_525
/5AmMC6/CCC AAC CAG TAC TGC
106534563
8712
60.5






ATT TCT TGG AGA A





 


AJ_P6
85653319
D10
AJ_526
/5AmMC6/CCC AAC AAG CCT AGT
106534564
8712
60.5






TCT GGT TGT ACA A





 


AJ_P6
85653320
D11
AJ_527
/5AmMC6/CCC AAC AGA CCT ACC
106534565
8672
60.5






TTT GTT GTA GCA A





 


AJ_P6
85653321
D12
AJ_528
/5AmMC6/CCC AAG AAC CCT TCT
106534566
8681
60.9






TTG ACT GCA AGA A





 


AJ_P6
85653322
E01
AJ_529
/5AmMC6/CCC AAA GTC GTT TAG
106534567
8672
60.2






TCC TCT GAC CAA A





 


AJ_P6
85653323
E02
AJ_530
/5AmMC6/CCC AAA GTC TCT TCG TTC
106534568
8712
60.2






AAC TGG AGA A





 


AJ_P6
85653324
E03
AJ_531
/5AmMC6/CCC AAC GCA TTC TTA
106534569
8714
58.6






ACA GAG ACA GTA A





 


AJ_P6
85653325
E04
AJ_532
/5AmMC6/CCC AAC GAG TCT CTT
106534570
8770
59.4






GAG AGG AAA CTA A





 


AJ_P6
85653326
E05
AJ_533
/5AmMC6/CCC AAC GTA GTG AGT
106534571
8755
61






AGA CGT ACA CCA A





 


AJ_P6
85653327
E06
AJ_534
/5AmMC6/CCC AAA AAG CTT GTT
106534572
8696
59.6






ACC TTC TGC AGA A





 


AJ_P6
85653328
E07
AJ_535
/5AmMC6/CCC AAA CTT TGT ACT
106534573
8745
59.1






GGA GTA GCC AAA A





 


AJ_P6
85653329
E08
AJ_536
/5AmMC6/CCC AAG CTT ACC TCT
106534574
8705
58.9






TAA GTG CAA GAA A





 


AJ_P6
85653330
E09
AJ_537
/5AmMC6/CCC AAG AAC CTC TTA
106534575
8723
58.9






AAG CTA AGC GAA A





 


AJ_P6
85653331
E10
AJ_538
/5AmMC6/CCC AAG ACC TAA ACA
106534576
8739
60.4






AGC TTG AGT CGA A





 


AJ_P6
85653332
E11
AJ_539
/5AmMC6/CCC AAT TTG CAT AGG
106534577
8687
59.5






TTC TTC CAA CGA A





 


AJ_P6
85653333
E12
AJ_540
/5AmMC6/CCC AAG CAA GTT GCA
106534578
8672
61.1






TTC CTC TCA TGA A





 


AJ_P6
85653334
F01
AJ_541
/5AmMC6/CCC AAT CGG TAC ACG
106534579
8739
59.9






ACA TAC ATG AGA A





 


AJ_P6
85653335
F02
AJ_542
/5AmMC6/CCC AAA CCT CTG TTT CTG
106534580
8712
60.2






AGT CGA AGA A





 


AJ_P6
85653336
F03
AJ_543
/5AmMC6/CCC AAA CAC GTG TTG
106534581
8745
59.3






GCT AGT CTA AAA A





 


AJ_P6
85653337
F04
AJ_544
/5AmMC6/CCC AAC GGT TTA AGC
106534582
8672
61.3






CTT TCA CCA TGA A





 


AJ_P6
85653338
F05
AJ_545
/5AmMC6/CCC AAC GGT TCA TGG
106534583
8786
61.7






ACT AAC TGA GGA A





 


AJ_P6
85653339
F06
AJ_546
/5AmMC6/CCC AAA CCG TTC AGT
106534584
8721
61.4






TTC ACA TGG GAA A





 


AJ_P6
85653340
F07
AJ_547
/5AmMC6/CCC AAG ACC TCT CCA
106534585
8657
61






CTT GAC TGT AGA A





 


AJ_P6
85653341
F08
AJ_548
/5AmMC6/CCC AAG TCT TTA CCT
106534586
8712
59.7






CAG TGT AGC AGA A





 


AJ_P6
85653342
F09
AJ_549
/5AmMC6/CCC AAA CAG CTG AGT
106534587
8690
60.2






CCT TCC ATA AGA A





 


AJ_P6
85653343
F10
AJ_550
/5AmMC6/CCC AAA ACT GTC ATT
106534588
8672
60.6






GCC TTC CTA GGA A





 


AJ_P6
85653344
F11
AJ_551
/5AmMC6/CCC AAG TCC ATT CAT
106534589
8712
60.6






TCG TTC GAA GGA A





 


AJ_P6
85653345
F12
AJ_552
/5AmMC6/CCC AAG TCA CCT CTT
106534590
8737
61.6






GGT AGT AAG GCA A





 


AJ_P6
85653346
G01
AJ_553
/5AmMC6/CCC AAC CAT CAG CTT
106534591
8712
60.9






TAG TTG GTG ACA A





 


AJ_P6
85653347
G02
AJ_554
/5AmMC6/CCC AAG TTA CCT GAC
106534592
8666
61.7






TCC ACT GGA CAA A





 


AJ_P6
85653348
G03
AJ_555
/5AmMC6/CCC AAA GTT GGC ATC
106534593
8727
60.1






TTT GTC GTC AAA A





 


AJ_P6
85653349
G04
AJ_556
/5AmMC6/CCC AAA CGT TGT GTC TTT
106534594
8687
59.4






AAC ATC CGA A





 


AJ_P6
85653350
G05
AJ_557
/5AmMC6/CCC AAC AGT TTG GCT
106534595
8712
61.5






TTG ACA TCA CGA A





 


AJ_P6
85653351
G06
AJ_558
/5AmMC6/CCC AAA CGG TTT GCA
106534596
8687
60.1






ACT CAT TCT TGA A





 


AJ_P6
85653352
G07
AJ_559
/5AmMC6/CCC AAG ACG ACT GTT
106534597
8672
59.8






TAC TTC CTC AGA A





 


AJ_P6
85653353
G08
AJ_560
/5AmMC6/CCC AAG GAC TCC ATT
106534598
8657
61.9






TCG ACT TCG ACA A





 


AJ_P6
85653354
G09
AJ_561
/5AmMC6/CCC AAA TCA AGT CTA
106534599
8763
58






GAC AGA AGG CTA A





 


AJ_P6
85653355
G10
AJ_562
/5AmMC6/CCC AAG TCG TCA TCA
106534600
8699
60.4






GCA AGA AAC CTA A





 


AJ_P6
85653356
G11
AJ_563
/5AmMC6/CCC AAT CGT GTA CAT
106534601
8754
59.1






GGA AAG CAC ATA A





 


AJ_P6
85653357
G12
AJ_564
/5AmMC6/CCC AAC TTT GAA GCA
106534602
8754
59.1






TGG AGA ACA CTA A





 


AJ_P6
85653358
H01
AJ_565
/5AmMC6/CCC AAA AGT CCT CTG
106534603
8727
58.6






TTT AGT TAG CGA A





 


AJ_P6
85653359
H02
AJ_566
/5AmMC6/CCC AAG TAA CCA AAC
106534604
8699
60.5






CAT GCT AGT CGA A





 


AJ_P6
85653360
H03
AJ_567
/5AmMC6/CCC AAG GAC ATT GAC
106534605
8675
62.4






TCA CCA TCA GCA A





 


AJ_P6
85653361
H04
AJ_568
/5AmMC6/CCC AAT GGG TAC TGC
106534606
8730
60






ATA CAC CAT AGA A





 


AJ_P6
85653362
H05
AJ_569
/5AmMC6/CCC AAA GAA CTC GTC
106534607
8696
58.8






TTC ATT TAC GGA A





 


AJ_P6
85653363
H06
AJ_570
/5AmMC6/CCC AAA GGT CTT TGT
106534608
8752
59.5






CCT AGT ACG AGA A





 


AJ_P6
85653364
H07
AJ_571
/5AmMC6/CCC AAC ATG GTT AAG
106534609
8770
60.3






GTC AAC TCG AGA A





 


AJ_P6
85653365
H08
AJ_572
/5AmMC6/CCC AAG CTT GTA ACG
106534610
8672
59.9






ACT TAC TCT CGA A





 


AJ_P6
85653366
H09
AJ_573
/5AmMC6/CCC AAG ACC ACT CTC
106534611
8657
61.7






CTA GCA TTT GGA A





 


AJ_P6
85653367
H10
AJ_574
/5AmMC6/CCC AAG TCC ATT CCC
106534612
8697
62.2






ATT GGT AGC AGA A





 


AJ_P6
85653368
H11
AJ_575
/5AmMC6/CCC AAC ACT CTG TGT
106534613
8737
61.3






CGT ACA TAG GGA A





 


AJ_P6
85653369
H12
AJ_576
/5AmMC6/CCC AAA CTT GTG TGG
106534614
8706
62.8






AAA CCG TAC CCA A





 


AJ_P7
85653371
A01
AJ_577
/5AmMC6/CCC AAA TGC CTT GGT
106534711
8761
61






GTC ATA CAG GAA A





 


AJ_P7
85653372
A02
AJ_578
/5AmMC6/CCC AAT CGG AAG TCA
106534712
8763
57.8






GAC TAG AAA CTA A





 


AJ_P7
85653373
A03
AJ_579
/5AmMC6/CCC AAC CAG TAC CAG
106534713
8755
61






AGG TGA AGT CTA A





 


AJ_P7
85653374
A04
AJ_580
/5AmMC6/CCC AAC ATA AAG GGA
106534714
8763
58.4






AAC TGA GCT CTA A





 


AJ_P7
85653375
A05
AJ_581
/5AmMC6/CCC AAC TAA GAG GAG
106534715
8779
59.6






AAC TCC AGT TGA A





 


AJ_P7
85653376
A06
AJ_582
/5AmMC6/CCC AAC TAG GAA GTT
106534716
8681
59.5






TAC TCC ACT CGA A





 


AJ_P7
85653377
A07
AJ_583
/5AmMC6/CCC AAC AAC GTC TGC
106534717
8730
60.3






TAA AGT AGG TCA A





 


AJ_P7
85653378
A08
AJ_584
/5AmMC6/CCC AAC GTC ATC AAC
106534718
8714
58.4






ATA GTA GGC TAA A





 


AJ_P7
85653379
A09
AJ_585
/5AmMC6/CCC AAA TCG TCA CTA
106534719
8763
57.3






GAG AGA GAA CTA A





 


AJ_P7
85653380
A10
AJ_586
/5AmMC6/CCC AAC TTG TCA CAT
106534720
8730
60






GAA GGA GAC CTA A





 


AJ_P7
85653381
A11
AJ_587
/5AmMC6/CCC AAG GAG ACT CTA
106534721
8739
59.5






GAA ACT TCC GAA A





 


AJ_P7
85653382
A12
AJ_588
/5AmMC6/CCC AAG AGT TAC GCT
106534722
8672
59.7






TCT ACT TCC AGA A





 


AJ_P7
85653383
B01
AJ_589
/5AmMC6/CCC AAA CCA GTC CTT
106534723
8746
61.5






AAG GGT AGG TCA A





 


AJ_P7
85653384
B02
AJ_590
/5AmMC6/CCC AAA AGC CTA GAA
106534724
8723
58.8






CAT TAC ATC GGA A





 


AJ_P7
85653385
B03
AJ_591
/5AmMC6/CCC AAG CTG AAA GCA
106534725
8690
61.1






CTC CAT CAT TGA A





 


AJ_P7
85653386
B04
AJ_592
/5AmMC6/CCC AAT CAG TGT GAC
106534726
8657
61.1






TCC ATC CCT AGA A





 


AJ_P7
85653387
B05
AJ_593
/5AmMC6/CCC AAG CTA CTT AAC
106534727
8687
58.6






TCT GTT TCG GAA A





 


AJ_P7
85653388
B06
AJ_594
/5AmMC6/CCC AAA TGC TTT CAC
106534728
8752
60.6






TGG TCT AGG GAA A





 


AJ_P7
85653389
B07
AJ_595
/5AmMC6/CCC AAC AGT TGT TCG
106534729
8712
60.9






TTC ATG ACC AGA A





 


AJ_P7
85653390
B08
AJ_596
/5AmMC6/CCC AAT CAC GAA ACG
106534730
8739
59.8






ACT ACT TAG GGA A





 


AJ_P7
85653391
B09
AJ_597
/5AmMC6/CCC AAC ATT GTT TGG TTC
106534731
8727
60.1






ATC AAG CGA A





 


AJ_P7
85653392
B10
AJ_598
/5AmMC6/CCC AAA TTC TTG TGG
106534732
8736
59.8






TAC AAC ATG CGA A





 


AJ_P7
85653393
B11
AJ_599
/5AmMC6/CCC AAC CTG ACC AAC
106534733
8672
61






GGT TCA TTT GTA A





 


AJ_P7
85653394
B12
AJ_600
/5AmMC6/CCC AAG ACC ATT ACG
106534734
8672
60.8






TCT TGC CTT GAA A





 


AJ_P7
85653395
C01
AJ_601
/5AmMC6/CCC AAG CCA TAC CTC
106534735
8672
60.8






ATT GAG CTT TGA A





 


AJ_P7
85653396
C02
AJ_602
/5AmMC6/CCC AAA GGA CTC TTC
106534736
8657
61.7






CGT AAC CTG TCA A





 


AJ_P7
85653397
C03
AJ_603
/5AmMC6/CCC AAG GAG TGC ATT
106534737
8761
60.8






TCG TAA CCT GAA A





 


AJ_P7
85653398
C04
AJ_604
/5AmMC6/CCC AAT CAC AAG CGA
106534738
8754
58.6






AAG TAG TGT CTA A





 


AJ_P7
85653399
C05
AJ_605
/5AmMC6/CCC AAT CGA AGA GAC
106534739
8770
60.1






GAC TTG AGT TCA A





 


AJ_P7
85653400
C06
AJ_606
/5AmMC6/CCC AAA TGG CTT TGG
106534740
8761
61.2






TAC AAC TGA CGA A





 


AJ_P7
85653401
C07
AJ_607
/5AmMC6/CCC AAG AGA CGT TGG
106534741
8755
61.6






AAC ACC TAC TGA A





 


AJ_P7
85653402
C08
AJ_608
/5AmMC6/CCC AAG AAA GCT GTT
106534742
8699
61.1






CAA ACC TCA CGA A





 


AJ_P7
85653403
C09
AJ_609
/5AmMC6/CCC AAG TGA GTC TTC
106534743
8761
60.4






GAA ACT TCG GAA A





 


AJ_P7
85653404
C10
AJ_610
/5AmMC6/CCC AAC CAG TGT TAA
106534744
8786
62.4






CGG AAC TTG GGA A





 


AJ_P7
85653405
C11
AJ_611
/5AmMC6/CCC AAC AGG TGT ACT
106534745
8777
61.3






TGG TAC TAC GGA A





 


AJ_P7
85653406
C12
AJ_612
/5AmMC6/CCC AAG TAC CAT CCT
106534746
8672
59.8






TAC GTA GCT TGA A





 


AJ_P7
85653407
D01
AJ_613
/5AmMC6/CCC AAG CTA CTT CCA
106534747
8706
60.9






CTA GGT ACA GGA A





 


AJ_P7
85653408
D02
AJ_614
/5AmMC6/CCC AAG TAC CTC AAC
106534748
8699
60.1






AAG TCA AGG CTA A





 


AJ_P7
85653409
D03
AJ_615
/5AmMC6/CCC AAG TAC CCA AGA
106534749
8739
59.8






GAC TAA GCT TGA A





 


AJ_P7
85653410
D04
AJ_616
/5AmMC6/CCC AAT GAA CCA AAC
106534750
8699
61






ACT GAC CTG TGA A





 


AJ_P7
85653411
D05
AJ_617
/5AmMC6/CCC AAG TGC ACA TCG
106534751
8699
60.8






AAC CAA CTT AGA A





 


AJ_P7
85653412
D06
AJ_618
/5AmMC6/CCC AAT GCT TAG CGT
106534752
8696
58.2






ACT ACC ATT AGA A





 


AJ_P7
85653413
D07
AJ_619
/5AmMC6/CCC AAG TTT GAC GTT
106534753
8681
61.2






CAA CCA TCA CGA A





 


AJ_P7
85653414
D08
AJ_620
/5AmMC6/CCC AAT TTA GCT TGT
106534754
8712
60.2






CCA CTC AGA GGA A





 


AJ_P7
85653415
D09
AJ_621
/5AmMC6/CCC AAC GCT ACT TTC TTA
106534755
8687
58.4






GTT AGA GCA A





 


AJ_P7
85653416
D10
AJ_622
/5AmMC6/CCC AAA AGC CTT TCC
106534756
8672
60.9






ACT GTT ACT GGA A





 


AJ_P7
85653417
D11
AJ_623
/5AmMC6/CCC AAC CTG TTA CCT
106534757
8697
61.9






CAG ACA TTG GGA A





 


AJ_P7
85653418
D12
AJ_624
/5AmMC6/CCC AAC GTC ATT TAG
106534758
8752
59.6






GTC TCT AAG GGA A





 


AJ_P7
85653419
E01
AJ_625
/5AmMC6/CCC AAA CGT CTT GGG
106534759
8712
60.2






TTA CAC TAC TGA A





 


AJ_P7
85653420
E02
AJ_626
/5AmMC6/CCC AAT CAC AGA ACC
106534760
8690
60.8






AGT CAG CTT TGA A





 


AJ_P7
85653421
E03
AJ_627
/5AmMC6/CCC AAG TGG TAC TCT
106534761
8697
60.9






CGT AAC TCC AGA A





 


AJ_P7
85653422
E04
AJ_628
/5AmMC6/CCC AAG AAC TCC TAC
106534762
8675
61.2






CAA GAC TCG TGA A





 


AJ_P7
85653423
E05
AJ_629
/5AmMC6/CCC AAT TTG ACT TGA
106534763
8705
59.7






ACG CAT AAC CGA A





 


AJ_P7
85653424
E06
AJ_630
/5AmMC6/CCC AAT TGA GAC CTC
106534764
8699
59.8






ACG AGA ACA CTA A





 


AJ_P7
85653425
E07
AJ_631
/5AmMC6/CCC AAA CAA AGT CAT
106534765
8745
59.8






TGG GTT CGC TAA A





 


AJ_P7
85653426
E08
AJ_632
/5AmMC6/CCC AAT CGA ACA AAC
106534766
8699
60.4






CTA GAG TGC TCA A





 


AJ_P7
85653427
E09
AJ_633
/5AmMC6/CCC AAG GTC TTA GCT
106534767
8681
59.8






ACA ACC TCA TGA A





 


AJ_P7
85653428
E10
AJ_634
/5AmMC6/CCC AAG CTT TGA AGC
106534768
8681
60.7






CTT CCA ACT AGA A





 


AJ_P7
85653429
E11
AJ_635
/5AmMC6/CCC AAT ACA GGT GTC
106534769
8699
60.5






ACA AAC TCA CGA A





 


AJ_P7
85653430
E12
AJ_636
/5AmMC6/CCC AAC CGT TCA TAA
106534770
8699
60.4






CAA GGG AAC CTA A





 


AJ_P7
85653431
F01
AJ 637
/5AmMC6/CCC AAA GTA CCC AAA
106534771
8739
61






GCA TGT CTG GAA A





 


AJ_P7
85653432
F02
AJ_638
/5AmMC6/CCC AAA TGT TCT CTT TAC
106534772
8727
58.8






GCT AGG GAA A





 


AJ_P7
85653433
F03
AJ_639
/5AmMC6/CCC AAT TTG ACT TCA
106534773
8745
59.3






GAC GAA AGC TGA A





 


AJ_P7
85653434
F04
AJ_640
/5AmMC6/CCC AAT ACA GAA ACG
106534774
8723
59






ACA TAC GCT TGA A





 


AJ_P7
85653435
F05
AJ_641
/5AmMC6/CCC AAT CAC CAG AAG
106534775
8699
60






AAC TAC CTG TGA A





 


AJ_P7
85653436
F06
AJ_642
/5AmMC6/CCC AAT ACG AAC GAC
106534776
8770
60.2






AGG TCA TGG TTA A





 


AJ_P7
85653437
F07
AJ_643
/5AmMC6/CCC AAG AAC TCC AAC
106534777
8690
59.9






CAT GTA GTC GTA A





 


AJ_P7
85653438
F08
AJ_644
/5AmMC6/CCC AAA TTG CGT TCT
106534778
8696
59.6






TCA GTA CAC GAA A





 


AJ_P7
85653439
F09
AJ_645
/5AmMC6/CCC AAA TCT GCT TCC TGT
106534779
8672
60






AGT ACA CGA A





 


AJ_P7
85653440
F10
AJ_646
/5AmMC6/CCC AAG GTC ACT TGC
106534780
8675
62.3






AAC CTA GAA CCA A





 


AJ_P7
85653441
F11
AJ_647
/5AmMC6/CCC AAG GCT TAG TAC
106534781
8715
61.5






GAC AGT AAC CCA A





 


AJ_P7
85653442
F12
AJ_648
/5AmMC6/CCC AAC AAG TGA AGT
106534782
8795
62






GGT CTG ACC AGA A





 


AJ_P7
85653443
G01
AJ_649
/5AmMC6/CCC AAC AGA GTA GTG
106534783
8770
59.3






TGA CTA GCC TAA A





 


AJ_P7
85653444
G02
AJ_650
/5AmMC6/CCC AAT CAC AAG GAG
106534784
8754
59.1






TAG CAA CTT TGA A





 


AJ_P7
85653445
G03
AJ_651
/5AmMC6/CCC AAC CTG TAA GTG
106534785
8779
60.5






AAA CGA CTG GAA A





 


AJ_P7
85653446
G04
AJ_652
/5AmMC6/CCC AAC CCT AGT TGA
106534786
8755
61.8






GGA CAA ACT GGA A





 


AJ_P7
85653447
G05
AJ_653
/5AmMC6/CCC AAG GCA TCA CAC
106534787
8690
60.8






CTA GCA AGT TTA A





 


AJ_P7
85653448
G06
AJ_654
/5AmMC6/CCC AAG ACC TAC CCT
106534788
8666
60.9






ACA GAG CTT GTA A





 


AJ_P7
85653449
G07
AJ_655
/5AmMC6/CCC AAT TTC GTA ACA
106534789
8736
59.1






AGT TGG ACT CGA A





 


AJ_P7
85653450
G08
AJ_656
/5AmMC6/CCC AAT CAA AGA AAC
106534790
8763
59.8






AGG TTG CAC TGA A





 


AJ_P7
85653451
G09
AJ_657
/5AmMC6/CCC AAC GTC TTA GAG
106534791
8657
61.7






TCC TTG AAC CCA A





 


AJ_P7
85653452
G10
AJ_658
/5AmMC6/CCC AAT GCT GAA ACG
106534792
8687
59.8






TTT CCC TTG TAA A





 


AJ_P7
85653453
G11
AJ_659
/5AmMC6/CCC AAC AGG TTT GTT
106534793
8752
60.8






TGA CTC AGA CGA A





 


AJ_P7
85653454
G12
AJ_660
/5AmMC6/CCC AAC CTT CGA CAT
106534794
8723
59






AAA GAA AGC GTA A





 


AJ_P7
85653455
H01
AJ_661
/5AmMC6/CCC AAT GAA CCA TTA
106534795
8763
59.4






GCA AGC AAG GTA A





 


AJ_P7
85653456
H02
AJ_662
/5AmMC6/CCC AAT GAA CCT TGA
106534796
8739
61.3






GCA CAA ACT GGA A





 


AJ_P7
85653457
H03
AJ_663
/5AmMC6/CCC AAA GGG TTC TTG
106534797
8737
61.8






GAC AGT ACC TCA A





 


AJ_P7
85653458
H04
AJ_664
/5AmMC6/CCC AAC TGT AAA GGA
106534798
8721
59.5






GTT CGT ACC CTA A





 


AJ_P7
85653459
H05
AJ_665
/5AmMC6/CCC AAT CGA GAA GGA
106534799
8779
59.8






AGT CAC ACT GTA A





 


AJ_P7
85653460
H06
AJ_666
/5AmMC6/CCC AAC TAA AGG AAG
106534800
8770
60.4






TGT CAG CTG TCA A





 


AJ_P7
85653461
H07
AJ_667
/5AmMC6/CCC AAG CAC ATA AGG
106534801
8779
61.1






TCA AAC GTG TGA A





 


AJ_P7
85653462
H08
AJ_668
/5AmMC6/CCC AAC GTT GAA GGA
106534802
8779
61






ACA TTC ACA GGA A





 


AJ_P7
85653463
H09
AJ_669
/5AmMC6/CCC AAT GTG AGC TGA
106534803
8763
59.8






CAA ACA ACA TGA A





 


AJ_P7
85653464
H10
AJ_670
/5AmMC6/CCC AAG CTA CTC TAA
106534804
8675
61.4






CAC GAC TGG ACA A





 


AJ_P7
85653465
H11
AJ_671
/5AmMC6/CCC AAG CCT AAC CTT
106534805
8681
60.8






CAA GTG CAT GTA A





 


AJ_P7
85653466
H12
AJ_672
/5AmMC6/CCC AAG TAA ACA CCT
106534806
8730
59.9






CTA GGT TCG GAA A





 


AJ_P8
85653468
A01
AJ_673
/5AmMC6/CCC AAG TCT TGA CTC
106534807
8681
60






TCG ACT CGA AAA A





 


AJ_P8
85653469
A02
AJ_674
/5AmMC6/CCC AAC TGC AGA GTG
106534808
8779
61.1






GAC TTG ACA AAA A





 


AJ_P8
85653470
A03
AJ_675
/5AmMC6/CCC AAC AGC TCT GGT
106534809
8721
60






GTA CTT AAG ACA A





 


AJ_P8
85653471
A04
AJ_676
/5AmMC6/CCC AAT ACG AGA GAG
106534810
8779
59.6






ACG TTT ACG ACA A





 


AJ_P8
85653472
A05
AJ_677
/5AmMC6/CCC AAG TAC CCT ACT
106534811
8666
60.9






CTC GTC AAG GAA A





 


AJ_P8
85653473
A06
AJ_678
/5AmMC6/CCC AAT AAC GAC ACA
106534812
8699
60.5






ACT GGT TAC CGA A





 


AJ_P8
85653474
A07
AJ_679
/5AmMC6/CCC AAC ACG TCA TAA
106534813
8675
61.5






CGG TAG ACC TCA A





 


AJ_P8
85653475
A08
AJ_680
/5AmMC6/CCC AAT CCC AAG CAA
106534814
8699
60.2






CAG TCA GTA GTA A





 


AJ_P8
85653476
A09
AJ_681
/5AmMC6/CCC AAT AAA CGA ACA
106534815
8699
60.8






CCT GTG AGC TCA A





 


AJ_P8
85653477
A10
AJ_682
/5AmMC6/CCC AAG TTA CCA GAC
106534816
8699
60.2






TCA ACA ACG GTA A





 


AJ_P8
85653478
A11
AJ_683
/5AmMC6/CCC AAG TTA GCT TGA
106534817
8690
60.8






CCA ACC AAC GTA A





 


AJ_P8
85653479
A12
AJ_684
/5AmMC6/CCC AAG ACC ATC ACT
106534818
8675
60.7






ACA GGA GTC CTA A





 


AJ_P8
85653480
B01
AJ_685
/5AmMC6/CCC AAG TAC TCT TCT TAC
106534819
8712
59.3






GGT AGC AGA A





 


AJ_P8
85653481
B02
AJ_686
/5AmMC6/CCC AAT TTG CCA TCG
106534820
8714
60.4






ACA ACG TGA AAA A





 


AJ_P8
85653482
B03
AJ_687
/5AmMC6/CCC AAA GTC TCT TGG
106534821
8752
60.2






GTA CAA CGT GTA A





 


AJ_P8
85653483
B04
AJ_688
/5AmMC6/CCC AAT GAC CTT CTC GTT
106534822
8672
60.2






ACA ACG GTA A





 


AJ_P8
85653484
B05
AJ_689
/5AmMC6/CCC AAT ACC GTT CTG
106534823
8736
58.6






TTA AGA AGC GTA A





 


AJ_P8
85653485
B06
AJ_690
/5AmMC6/CCC AAA GTC CTT CCT
106534824
8672
59.6






CTA GTT ACG GAA A





 


AJ_P8
85653486
B07
AJ_691
/5AmMC6/CCC AAG CCA TAC AAC
106534825
8730
60.6






ATT GGA CTG GTA A





 


AJ_P8
85653487
B08
AJ_692
/5AmMC6/CCC AAC CTG AGA GGT
106534826
8761
59.8






AAG CTT GAC TTA A





 


AJ_P8
85653488
B09
AJ_693
/5AmMC6/CCC AAC ACC TAG TAG
106534827
8746
61.2






TCG TTG GAC AGA A





 


AJ_P8
85653489
B10
AJ_694
/5AmMC6/CCC AAG TAC ACT AAA
106534828
8723
59.6






CCG TTG CGA AAA A





 


AJ_P8
85653490
B11
AJ_695
/5AmMC6/CCC AAC CAC TGG TAC
106534829
8730
60.8






GGA AAG CTT TAA A





 


AJ_P8
85653491
B12
AJ_696
/5AmMC6/CCC AAG ACC ACT CTT
106534830
8746
61.2






TGA GGA GTA CGA A





 


AJ_P8
85653492
C01
AJ_697
/5AmMC6/CCC AAG ACT GAC CTT
106534831
8795
62






GGA AAG TAG GCA A





 


AJ_P8
85653493
C02
AJ_698
/5AmMC6/CCC AAC TCA CGT TAC
106534832
8739
60






GAA ACA GAG GTA A





 


AJ_P8
85653494
C03
AJ_699
/5AmMC6/CCC AAG CGT AAC GTC
106534833
8687
59.2






ATT TAC TTT CGA A





 


AJ_P8
85653495
C04
AJ_700
/5AmMC6/CCC AAC GAA CGT GTC
106534834
8687
59.7






ATT TCA CTT TGA A





 


AJ_P8
85653496
C05
AJ_701
/5AmMC6/CCC AAA TCT CTG GTG
106534835
8657
62.1






TCC ATC CGA ACA A





 


AJ_P8
85653497
C06
AJ_702
/5AmMC6/CCC AAA GCT TTG GAG
106534836
8761
61.1






TCT GTG ACA ACA A





 


AJ_P8
85653498
C07
AJ_703
/5AmMC6/CCC AAG GGT ACT AGG
106534837
8786
61.9






CTT GTG ACA ACA A





 


AJ_P8
85653499
C08
AJ_704
/5AmMC6/CCC AAT AGC GAA CAC
106534838
8699
60






CTA GTT ACG ACA A





 


AJ_P8
85653500
C09
AJ_705
/5AmMC6/CCC AAT CAC GAG TCC
106534839
8675
61.7






AAG AGT TAC CCA A





 


AJ_P8
85653501
C10
AJ_706
/5AmMC6/CCC AAT GAG AAC AAA
106534840
8763
59.1






GGC TAA CCG TTA A





 


AJ_P8
85653502
C11
AJ_707
/5AmMC6/CCC AAC TCG TCA TAG
106534841
8699
59.9






AAC ACC AAG GTA A





 


AJ_P8
85653503
C12
AJ_708
/5AmMC6/CCC AAC TCC ATG CAA
106534842
8723
59






GTA AAG AAC GTA A





 


AJ_P8
85653504
D01
AJ_709
/5AmMC6/CCC AAA TGT GAC TAC
106534843
8705
59.3






CGA AAC GCT TTA A





 


AJ_P8
85653505
D02
AJ_710
/5AmMC6/CCC AAG ACA AGT TGA
106534844
8699
60.8






CCA ACG CAT CTA A





 


AJ_P8
85653506
D03
AJ_711
/5AmMC6/CCC AAC TGC ACA GTT
106534845
8690
60.5






TAC AAC CTA GGA A





 


AJ_P8
85653507
D04
AJ_712
/5AmMC6/CCC AAG CTG ACT GTC
106534846
8672
59.8






TTA ACC CTT AGA A





 


AJ_P8
85653508
D05
AJ_713
/5AmMC6/CCC AAG GTC AAG TCG
106534847
8739
60






ACA AGC TAA CTA A





 


AJ_P8
85653509
D06
AJ_714
/5AmMC6/CCC AAC ACG TGA GTT
106534848
8675
62






CCA ACC CTA AGA A





 


AJ_P8
85653510
D07
AJ_715
/5AmMC6/CCC AAG CCA TAA CCA
106534849
8690
59.9






TCA GTC TGA GTA A





 


AJ_P8
85653511
D08
AJ_716
/5AmMC6/CCC AAG TCA ACA CAC
106534850
8699
60






TCA GCA GTA GTA A





 


AJ_P8
85653512
D09
AJ_717
/5AmMC6/CCC AAG TAC CTA CTC
106534851
8672
60






ATG CTT GCA GTA A





 


AJ_P8
85653513
D10
AJ_718
/5AmMC6/CCC AAA TGT ACG TAA
106534852
8723
59.2






AGC ACA AGC CTA A





 


AJ_P8
85653514
D11
AJ_719
/5AmMC6/CCC AAC GTG TAA AGG
106534853
8779
60






AAC TAG GCT ACA A





 


AJ_P8
85653515
D12
AJ_720
/5AmMC6/CCC AAG GTC ACT AAC
106534854
8675
61.4






TCA GGA ACT CCA A





 


AJ_P8
85653516
E01
AJ_721
/5AmMC6/CCC AAT TCG AAG TAA
106534855
8723
59.4






GCA ACA CCA TGA A





 


AJ_P8
85653517
E02
AJ_722
/5AmMC6/CCC AAT CGG AAG TGT
106534856
8779
60.6






AAA CTG GAC ACA A





 


AJ_P8
85653518
E03
AJ_723
/5AmMC6/CCC AAG ACT CAC AAA
106534857
8690
60.2






CCG TAC TTG GTA A





 


AJ_P8
85653519
E04
AJ_724
/5AmMC6/CCC AAC ATT CTG CAT
106534858
8770
60.2






AGG AGA CAG TGA A





 


AJ_P8
85653520
E05
AJ_725
/5AmMC6/CCC AAA CCC ATG CAC
106534859
8699
61.3






ATT GAG AAC TGA A





 


AJ_P8
85653521
E06
AJ_726
/5AmMC6/CCC AAT GGT CAG GAC
106534860
8739
59.7






TAA ACT ACC AGA A





 


AJ_P8
85653522
E07
AJ_727
/5AmMC6/CCC AAG CTT CCA GAA
106534861
8712
60.6






CTT TAC TTG GGA A





 


AJ_P8
85653523
E08
AJ_728
/5AmMC6/CCC AAG TTC AAC TCC
106534862
8675
62.3






AAC GTC AGG ACA A





 


AJ_P8
85653524
E09
AJ_729
/5AmMC6/CCC AAG TTA CTA CCA
106534863
8681
59.4






TAC GAC TCG TGA A





 


AJ_P8
85653525
E10
AJ_730
/5AmMC6/CCC AAC AGA CAT GCA
106534864
8699
60.5






CTT AAC TCA GGA A





 


AJ_P8
85653526
E11
AJ_731
/5AmMC6/CCC AAC TTG AAC CTA
106534865
8779
60.2






GAA AGG GTA GCA A





 


AJ_P8
85653527
E12
AJ_732
/5AmMC6/CCC AAG TCC TAC CTT
106534866
8730
58.8






AAG AGA CGA GTA A





 


AJ_P8
85653528
F01
AJ_733
/5AmMC6/CCC AAC AGT TAG GGA
106534867
8761
61.1






AGC TTT GCA TCA A





 


AJ_P8
85653529
F02
AJ_734
/5AmMC6/CCC AAC GTC TAG CTA
106534868
8745
58.2






GAA GAA GTT TCA A





 


AJ_P8
85653530
F03
AJ_735
/5AmMC6/CCC AAT TTA GTC ACC TCT
106534869
8672
60






GGA ACC GTA A





 


AJ_P8
85653531
F04
AJ_736
/5AmMC6/CCC AAC AGT GAA GGA
106534870
8730
60.9






ACC TTT CGT CAA A





 


AJ_P8
85653532
F05
AJ_737
/5AmMC6/CCC AAA GGC TTC CTT
106534871
8687
59.1






TCA GAC AGT TTA A





 


AJ_P8
85653533
F06
AJ_738
/5AmMC6/CCC AAA CGG TTG TTG
106534872
8761
60.9






AGT CGA ACC ATA A





 


AJ_P8
85653534
F07
AJ_739
/5AmMC6/CCC AAA CCT CTG AGT
106534873
8730
60.5






TGG CTA AAC AGA A





 


AJ_P8
85653535
F08
AJ_740
/5AmMC6/CCC AAG CAG TTG TAA
106534874
8779
60.3






GAC CAA GAC GTA A





 


AJ_P8
85653536
F09
AJ_741
/5AmMC6/CCC AAG AGA GCT ACC
106534875
8727
58.6






GTT TCT TTG TAA A





 


AJ_P8
85653537
F10
AJ_742
/5AmMC6/CCC AAA GGG TTC TCC
106534876
8761
60.4






AAG TTT ACA GGA A





 


AJ_P8
85653538
F11
AJ_743
/5AmMC6/CCC AAC GTT AGT GTG
106534877
8727
59.6






TTC AAG CTT CAA A





 


AJ_P8
85653539
F12
AJ_744
/5AmMC6/CCC AAC TCA CTG CAA
106534878
8739
60.8






AGG TAA AGG TCA A





 


AJ_P8
85653540
G01
AJ_745
/5AmMC6/CCC AAG AGC TCA CAA
106534879
8786
61.9






GGT GTT AGG TCA A





 


AJ_P8
85653541
G02
AJ_746
/5AmMC6/CCC AAC TGT CTA CTG
106534880
8752
60.4






AAG GAG TTT GCA A





 


AJ_P8
85653542
G03
AJ_747
/5AmMC6/CCC AAA GCT TCC TTT ACT
106534881
8687
58.3






GAC TAG TGA A





 


AJ_P8
85653543
G04
AJ_748
/5AmMC6/CCC AAC TGC TAC CCT
106534882
8681
60.1






TGA GTA AAG TCA A





 


AJ_P8
85653544
G05
AJ_749
/5AmMC6/CCC AAG CTC ATT CCC
106534883
8681
60.2






TTG AAC AGA GTA A





 


AJ_P8
85653545
G06
AJ_750
/5AmMC6/CCC AAG AGA CTG TGC
106534884
8715
61.9






ACA ACC CTT AGA A





 


AJ_P8
85653546
G07
AJ_751
/5AmMC6/CCC AAC GGT TAA CCT
106534885
8714
59.4






CAA GTG CTA AAA A





 


AJ_P8
85653547
G08
AJ_752
/5AmMC6/CCC AAA CCC TTG GGT
106534886
8755
61.7






AAG CTA GAG ACA A





 


AJ_P8
85653548
G09
AJ_753
/5AmMC6/CCC AAA TTG CTC ACG
106534887
8672
61.2






TTC TCA TGG ACA A





 


AJ_P8
85653549
G10
AJ_754
/5AmMC6/CCC AAC CCT AGG AAG
106534888
8690
60.3






CCA TCA GTT TAA A





 


AJ_P8
85653550
G11
AJ_755
/5AmMC6/CCC AAA CCG TTT GAA
106534889
8672
61.3






CCT TCT GGT CAA A





 


AJ_P8
85653551
G12
AJ_756
/5AmMC6/CCC AAT CCG AAG GAG
106534890
8739
60.7






AAC TTT GAC CAA A





 


AJ_P8
85653552
H01
AJ_757
/5AmMC6/CCC AAT TGA GTC TGA
106534891
8754
59.1






AGC AAC CAA GTA A





 


AJ_P8
85653553
H02
AJ_758
/5AmMC6/CCC AAC TGT TTA GAG
106534892
8727
58.7






TGA CAT TGC CTA A





 


AJ_P8
85653554
H03
AJ_759
/5AmMC6/CCC AAT ACT GTT AAG
106534893
8705
58.5






GCT ACA ACG CTA A





 


AJ_P8
85653555
H04
AJ_760
/5AmMC6/CCC AAA TCG GTT CGT
106534894
8672
60.1






TCA CTA CTC AGA A





 


AJ_P8
85653556
H05
AJ_761
/5AmMC6/CCC AAC CAA GGT TGG
106534895
8737
62






CTT AGT AGT CCA A





 


AJ_P8
85653557
H06
AJ_762
/5AmMC6/CCC AAG GCT ACA GAC
106534896
8672
60.6






TTT CCC ATT TGA A





 


AJ_P8
85653558
H07
AJ_763
/5AmMC6/CCC AAG AAC CTC ACG
106534897
8712
61






TGT GCT TGT TAA A





 


AJ_P8
85653559
H08
AJ_764
/5AmMC6/CCC AAG ACA TCC ACT
106534898
8672
60.5






CTT GTT TGA CGA A





 


AJ_P8
85653560
H09
AJ_765
/5AmMC6/CCC AAG GTA CAC ACC
106534899
8657
62.2






TTT GCC TTA CGA A





 


AJ_P8
85653561
H10
AJ_766
/5AmMC6/CCC AAC GAG TTG GAG
106534900
8779
60.1






TAA CAT ACG ACA A





 


AJ_P8
85653562
H11
AJ_767
/5AmMC6/CCC AAA CGG TTG TGG
106534901
8761
60.3






TAA CAT CCT AGA A





 


AJ_P8
85653563
H12
AJ_768
/5AmMC6/CCC AAG ACC TTG ACT
106586462
8795
61.7






GGA GAA ACG GTA A





 


AJ_P9
85653565
A01
AJ_769
/5AmMC6/CCC AAG CTC ACT ACC
106534903
8672
60.6






ATT GTC ATT GGA A





 


AJ_P9
85653566
A02
AJ_770
/5AmMC6/CCC AAT CCG TTA CGT
106534904
8770
60.6






GAA GGG TAA ACA A





 


AJ_P9
85653567
A03
AJ_771
/5AmMC6/CCC AAT ACA GAC TGC
106534905
8699
60.1






ACA CTC AGG TAA A





 


AJ_P9
85653568
A04
AJ_772
/5AmMC6/CCC AAT TTA CGT AGT
106534906
8696
59.3






CCA ACT TGC GAA A





 


AJ_P9
85653569
A05
AJ_773
/5AmMC6/CCC AAG ACC TTA CTA
106534907
8690
59.4






CCT GAA GCA GTA A





 


AJ_P9
85653570
A06
AJ_774
/5AmMC6/CCC AAC ATT GTT TCT CTG
106534908
8687
59.4






ACA AGC TGA A





 


AJ_P9
85653571
A07
AJ_775
/5AmMC6/CCC AAC AGC AGT TTA
106534909
8739
61






GCC AAG AAG TCA A





 


AJ_P9
85653572
A08
AJ_776
/5AmMC6/CCC AAG ACC TTG GAC
106534910
8657
60.9






TCT CTC TAA CGA A





 


AJ_P9
85653573
A09
AJ_777
/5AmMC6/CCC AAG TAC TTT CTT CCA
106534911
8672
60.1






GTC AGA GCA A





 


AJ_P9
85653574
A10
AJ_778
/5AmMC6/CCC AAT CAG ACA ACC
106534912
8681
60.7






TTG TTC ATC GGA A





 


AJ_P9
85653575
A11
AJ_779
/5AmMC6/CCC AAT CAC CTG TTG
106534913
8712
60.7






CAT TCA TAG GGA A





 


AJ_P9
85653576
A12
AJ_780
/5AmMC6/CCC AAT TTG CAG TGA
106534914
8714
59.8






ACA CCA ACA GTA A





 


AJ_P9
85653577
B01
AJ_781
/5AmMC6/CCC AAG TCT GCA GTA
106534915
8699
60.4






ACA CAC CAA GTA A





 


AJ_P9
85653578
B02
AJ_782
/5AmMC6/CCC AAT GTC TCA GTC
106534916
8672
59.7






TCC ACA TTA GGA A





 


AJ_P9
85653579
B03
AJ_783
/5AmMC6/CCC AAG TAC ACC ATT
106534917
8672
61.2






TCG CAT TTC GGA A





 


AJ_P9
85653580
B04
AJ_784
/5AmMC6/CCC AAG CTA CCA CTT
106534918
8730
60






TAG AAG TAG GCA A





 


AJ_P9
85653581
B05
AJ_785
/5AmMC6/CCC AAT CAC AAG GTT
106534919
8739
60






ACC ACA GGA GTA A





 


AJ_P9
85653582
B06
AJ_786
/5AmMC6/CCC AAC ACC ATG GAC
106534920
8715
61.9






ACT TCT AAG GGA A





 


AJ_P9
85653583
B07
AJ_787
/5AmMC6/CCC AAC CTG AAA GAG
106534921
8736
59.3






TTT CTT GCG TAA A





 


AJ_P9
85653584
B08
AJ_788
/5AmMC6/CCC AAG AGA CGT GTC
106534922
8706
61.3






ATC TCA TCC AGA A





 


AJ_P9
85653585
B09
AJ_789
/5AmMC6/CCC AAT AGC GTA GAC
106534923
8723
59.2






AAC TTC AAA GCA A





 


AJ_P9
85653586
B10
AJ_790
/5AmMC6/CCC AAA GTT CTC TCG TTC
106534924
8687
58.6






ATA GCT GAA A





 


AJ_P9
85653587
B11
AJ_791
/5AmMC6/CCC AAA TTG GTC TTC
106534925
8736
59.7






TGC ATA AAG CGA A





 


AJ_P9
85653588
B12
AJ_792
/5AmMC6/CCC AAT CGA AGG AGT
106534926
8761
58.8






AGT CTA CCT GTA A





 


AJ_P9
85653589
C01
AJ_793
/5AmMC6/CCC AAT CAG GAC TAC
106534927
8715
61.8






GGA AAG TTC CCA A





 


AJ_P9
85653590
C02
AJ_794
/5AmMC6/CCC AAC CGT AAC ATC
106534928
8675
62






CAT GAG ACG TCA A





 


AJ_P9
85653591
C03
AJ_795
/5AmMC6/CCC AAT GCG AAA GAG
106534929
8770
60.8






GTA CCG TTT ACA A





 


AJ_P9
85653592
C04
AJ_796
/5AmMC6/CCC AAG ACA CAT CCA
106534930
8675
62.1






ACT GGT GAC TCA A





 


AJ_P9
85653593
C05
AJ_797
/5AmMC6/CCC AAG ACC ATC CTT
106534931
8675
61.7






CAA GAG ACG TCA A





 


AJ_P9
85653594
C06
AJ_798
/5AmMC6/CCC AAG CTC TCA AGT
106534932
8690
60.6






CTA AAC AGT GCA A





 


AJ_P9
85653595
C07
AJ_799
/5AmMC6/CCC AAC AAA GTA GAA
106534933
8763
58.6






ACT CGT AGC TGA A





 


AJ_P9
85653596
C08
AJ_800
/5AmMC6/CCC AAC CAG AGT GTG
106534934
8795
61.3






AAC ACT AGG GTA A





 


AJ_P9
85653597
C09
AJ_801
/5AmMC6/CCC AAC CTC ATG AAG
106534935
8715
61.5






ACT CCA AGG GTA A





 


AJ_P9
85653598
C10
AJ_802
/5AmMC6/CCC AAA CCT GTG GAC
106534936
8666
62.1






ACT ACA CCT TGA A





 


AJ_P9
85653599
C11
AJ_803
/5AmMC6/CCC AAA GTT CAG AGT
106534937
8672
59.9






TCT CTC CAC TGA A





 


AJ_P9
85653600
C12
AJ_804
/5AmMC6/CCC AAG CTA CTT TCA
106534938
8721
60.4






ACT GAC AGT GGA A





 


AJ_P9
85653601
D01
AJ_805
/5AmMC6/CCC AAG CCA TCT TCT
106534939
8681
60.1






ACT GAA CGG TAA A





 


AJ_P9
85653602
D02
AJ_806
/5AmMC6/CCC AAT GTT TCA GTC
106534940
8687
59.4






CAT TGA ACG CTA A





 


AJ_P9
85653603
D03
AJ_807
/5AmMC6/CCC AAA TTG CTT CTC
106534941
8687
59.1






ACG TCA TTA GGA A





 


AJ_P9
85653604
D04
AJ_808
/5AmMC6/CCC AAT GGG AAC TCT
106534942
8739
60.8






GAA ACA TCC GAA A





 


AJ_P9
85653605
D05
AJ_809
/5AmMC6/CCC AAT CGT AGA GTC
106534943
8723
58.4






AAA CCA CAA GTA A





 


AJ_P9
85653606
D06
AJ_810
/5AmMC6/CCC AAC AGG TGT CGT
106534944
8786
62.5






GTG AAA CAG TCA A





 


AJ_P9
85653607
D07
AJ_811
/5AmMC6/CCC AAG GTC ATT AAG
106534945
8657
62






CCT TCG ACT CCA A





 


AJ_P9
85653608
D08
AJ_812
/5AmMC6/CCC AAC TTG AAG TGA
106534946
8779
61.3






AGG CAA CCA TGA A





 


AJ_P9
85653609
D09
AJ_813
/5AmMC6/CCC AAC AAC TAG GAG
106534947
8761
60.1






TGC TCT GGT TAA A





 


AJ_P9
85653610
D10
AJ_814
/5AmMC6/CCC AAG ACC ATA GCA
106534948
8675
61.9






TCC AAG TCG TCA A





 


AJ_P9
85653611
D11
AJ_815
/5AmMC6/CCC AAT CGA GAA ACA
106534949
8723
58.4






CCT GTA CAA GTA A





 


AJ_P9
85653612
D12
AJ_816
/5AmMC6/CCC AAC AGT CTT TAA
106534950
8754
58.3






GCA GAA GGA CTA A





 


AJ_P9
85653613
E01
AJ_817
/5AmMC6/CCC AAC GTC AAC TAC
106534951
8699
59.8






ACA GAA GGT CTA A





 


AJ_P9
85653614
E02
AJ_818
/5AmMC6/CCC AAG TCG ACA ACA
106534952
8730
60






GCA TTA GGT CTA A





 


AJ_P9
85653615
E03
AJ_819
/5AmMC6/CCC AAT TGG TCA GAA
106534953
8687
59.9






CTT TCC TTG CAA A





 


AJ_P9
85653616
E04
AJ_820
/5AmMC6/CCC AAC CTA GGT CAA
106534954
8752
60.5






GTT TAG GTT GCA A





 


AJ_P9
85653617
E05
AJ_821
/5AmMC6/CCC AAG TCA TCT GCA
106534955
8666
61.6






TCC ACA CTA GGA A





 


AJ_P9
85653618
E06
AJ_822
/5AmMC6/CCC AAA TCG CTT GAA
106534956
8690
61






CCA TAC CAT GGA A





 


AJ_P9
85653619
E07
AJ_823
/5AmMC6/CCC AAA TCT GAA CTG
106534957
8763
58.8






AGG AAC AAG CTA A





 


AJ_P9
85653620
E08
AJ_824
/5AmMC6/CCC AAC GTG AGC ATC
106534958
8770
61.2






AGG AAC ATT TGA A





 


AJ_P9
85653621
E09
AJ_825
/5AmMC6/CCC AAT CCC TAG TTC
106534959
8697
61.2






CAG TCA TGA GGA A





 


AJ_P9
85653622
E10
AJ_826
/5AmMC6/CCC AAC TCC TAG TCC
106534960
8657
60.7






TGT AGT CCA GAA A





 


AJ_P9
85653623
E11
AJ_827
/5AmMC6/CCC AAG AGT CAA CTC
106534961
8699
60.2






CAT GAA AGC CTA A





 


AJ_P9
85653624
E12
AJ_828
/5AmMC6/CCC AAG GTA GTC TCA
106534962
8755
61






GAG AAC ACC TGA A





 


AJ_P9
85653625
F01
AJ_829
/5AmMC6/CCC AAG CTG TAG GAC
106534963
8779
59.8






ATA AGA ACC GTA A





 


AJ_P9
85653626
F02
AJ_830
/5AmMC6/CCC AAG TCC AAC TGA
106534964
8739
60.4






AAC AGA GCT GTA A





 


AJ_P9
85653627
F03
AJ_831
/5AmMC6/CCC AAG TGC AAC TAC
106534965
8795
62.1






AGG ACA GTG TGA A





 


AJ_P9
85653628
F04
AJ_832
/5AmMC6/CCC AAT GAA ACA GAC
106534966
8763
59.3






AAG TAG CGT TCA A





 


AJ_P9
85653629
F05
AJ_833
/5AmMC6/CCC AAA AAC TGT AGC
106534967
8696
59.5






TTT CCC TTG GAA A





 


AJ_P9
85653630
F06
AJ_834
/5AmMC6/CCC AAT CCG TAG AGC
106534968
8761
60






AGT GAG TTT ACA A





 


AJ_P9
85653631
F07
AJ_835
/5AmMC6/CCC AAG GTT CAT GCA
106534969
8672
60.6






TCC TCT TCA AGA A





 


AJ_P9
85653632
F08
AJ_836
/5AmMC6/CCC AAA CCT TTG TGG
106534970
8761
61.3






AGT CAA GCA TGA A





 


AJ_P9
85653633
F09
AJ_837
/5AmMC6/CCC AAA CCT TTG TGA
106534971
8736
59.7






GCA GAG CAT TTA A





 


AJ_P9
85653634
F10
AJ_838
/5AmMC6/CCC AAA CTG TTT CCC TTA
106534972
8672
60.5






GAG CAG TCA A





 


AJ_P9
85653635
F11
AJ_839
/5AmMC6/CCC AAG CTG TAG GAG
106534973
8752
59.4






TTA CAT CTC TGA A





 


AJ_P9
85653636
F12
AJ_840
/5AmMC6/CCC AAG TGG ACA CTC
106534974
8706
61.3






CAG AAC TCT GTA A





 


AJ_P9
85653637
G01
AJ_841
/5AmMC6/CCC AAC GTC ATC TGA
106534975
8699
59.8






CAG AAC AGA CTA A





 


AJ_P9
85653638
G02
AJ_842
/5AmMC6/CCC AAG TCC AAC GAA
106534976
8699
60.8






GCA TGA CAC TTA A





 


AJ_P9
85653639
G03
AJ_843
/5AmMC6/CCC AAA GCC TAA AGC
106534977
8721
61.2






CTT TGG GTT ACA A





 


AJ_P9
85653640
G04
AJ_844
/5AmMC6/CCC AAC CGT TCA AAC
106534978
8699
60.4






GAC TAA GAG TCA A





 


AJ_P9
85653641
G05
AJ_845
/5AmMC6/CCC AAT CGG AAC ACC
106534979
8672
61.5






TTT GGT TTC CAA A





 


AJ_P9
85653642
G06
AJ_846
/5AmMC6/CCC AAT GAC CAT CAT
106534980
8687
60






GTT TGG CTT CAA A





 


AJ_P9
85653643
G07
AJ_847
/5AmMC6/CCC AAG ACC ATG AGC
106534981
8672
60.5






TCT CTT GTT CAA A





 


AJ_P9
85653644
G08
AJ_848
/5AmMC6/CCC AAC TAG GTG AAG
106534982
8755
61.9






TGA CAG CAT CCA A





 


AJ_P9
85653645
G09
AJ_849
/5AmMC6/CCC AAC AAG TTA GGA
106534983
8779
60.4






GAC TGA CTG CAA A





 


AJ_P9
85653646
G10
AJ_850
/5AmMC6/CCC AAT CAG CAC ACG
106534984
8714
58.6






AGT TCT AGT AAA A





 


AJ_P9
85653647
G11
AJ_851
/5AmMC6/CCC AAA CGT CAC CTA
106534985
8737
62.1






GGT TGG GTT ACA A





 


AJ_P9
85653648
G12
AJ_852
/5AmMC6/CCC AAA CCT TGT CTC TTA
106534986
8672
60.6






GCC ATG GAA A





 


AJ_P9
85653649
H01
AJ_853
/5AmMC6/CCC AAA CCT TGT TAC
106534987
8712
60.6






TGT GCT AGA GCA A





 


AJ_P9
85653650
H02
AJ_854
/5AmMC6/CCC AAA CAG AGT GCT
106534988
8681
60.8






TCC AAC TTC TGA A





 


AJ_P9
85653651
H03
AJ_855
/5AmMC6/CCC AAT CGT TCA CGA
106534989
8761
60.2






AGT AGG GTT ACA A





 


AJ_P9
85653652
H04
AJ_856
/5AmMC6/CCC AAA AAC ATG TTC
106534990
8705
60.1






CGT AGT TGC CAA A





 


AJ_P9
85653653
H05
AJ_857
/5AmMC6/CCC AAT GAC CAC AAC
106534991
8699
60.9






ATA GCA TGT CGA A





 


AJ_P9
85653654
H06
AJ_858
/5AmMC6/CCC AAG CAT AAA CAC
106534992
8739
60.2






TCT GGA CAG GTA A





 


AJ_P9
85653655
H07
AJ_859
/5AmMC6/CCC AAG CTA ACA ACC
106534993
8699
59.7






ATC GAG AGT CTA A





 


AJ_P9
85653656
H08
AJ_860
/5AmMC6/CCC AAG TGA AAC TCA
106534994
8699
59.7






CAC GAG ACT CTA A





 


AJ_P9
85653657
H09
AJ_861
/5AmMC6/CCC AAG TAA CAA ACC
106534995
8739
60.9






CAT GAG CTG TGA A





 


AJ_P9
85653658
H10
AJ_862
/5AmMC6/CCC AAG TCG ACA TCA
106534996
8755
61.9






CAG TCA AGG TGA A





 


AJ_P9
85653659
H11
AJ_863
/5AmMC6/CCC AAG AAC TCT CTC
106534997
8672
60.4






TGC ACA TTG TGA A





 


AJ_P9
85653660
H12
AJ_864
/5AmMC6/CCC AAC TGC ACA CAT
106534998
8687
60.1






GGT TTC TTT GAA A





 


AJ_P10
85653662
A01
AJ_865
/5AmMC6/CCC AAT AAA GCA CTT
106534999
8754
58.7






TGA GAG TAC CGA A





 


AJ_P10
85653663
A02
AJ_866
/5AmMC6/CCC AAA TCG CTT GTT
106535000
8687
59.1






TAA CCT ACT GGA A





 


AJ_P10
85653664
A03
AJ_867
/5AmMC6/CCC AAC GTT GAG TTT
106535001
8745
59






AAG CTA CCA GAA A





 


AJ_P10
85653665
A04
AJ_868
/5AmMC6/CCC AAG TTT CAC TAC
106535002
8681
60






ACG ACT TCG AGA A





 


AJ_P10
85653666
A05
AJ_869
/5AmMC6/CCC AAT GGA GAC AGT
106535003
8712
60.4






CTT CCC TTT GAA A





 


AJ_P10
85653667
A06
AJ_870
/5AmMC6/CCC AAG TTT CAC TGC
106535004
8712
61.1






ACT TCA AGG TGA A





 


AJ_P10
85653668
A07
AJ_871
/5AmMC6/CCC AAC CAG TCT GGT
106535005
8657
61.2






TCT ACT ACA CGA A





 


AJ_P10
85653669
A08
AJ_872
/5AmMC6/CCC AAA TTC TCG TTC TCA
106535006
8712
59.9






GAG TCA GGA A





 


AJ_P10
85653670
A09
AJ_873
/5AmMC6/CCC AAG TTA CCA ACA
106535007
8699
60.1






CCT GAG AAG CTA A





 


AJ_P10
85653671
A10
AJ_874
/5AmMC6/CCC AAA CTA CTG TCA
106535008
8779
60.1






AAG GAG TAG GCA A





 


AJ_P10
85653672
A11
AJ_875
/5AmMC6/CCC AAG TTC CCA AGA
106535009
8675
62






CCT ACA AGC TGA A





 


AJ_P10
85653673
A12
AJ_876
/5AmMC6/CCC AAT TTA GCC TAA
106535010
8714
59






CAG CAA CAG GTA A





 


AJ_P10
85653674
B01
AJ_877
/5AmMC6/CCC AAA TCT GTT CTC TGC
106535011
8687
59






AAA GTC GTA A





 


AJ_P10
85653675
B02
AJ_878
/5AmMC6/CCC AAA GTC CTT GTC
106535012
8681
60.3






TCA AAC TCA GGA A





 


AJ_P10
85653676
B03
AJ_879
/5AmMC6/CCC AAA TCT TGT GTG
106535013
8736
59.3






TCG AAG CAA CTA A





 


AJ_P10
85653677
B04
AJ_880
/5AmMC6/CCC AAG TGC AAC TGG
106535014
8770
60.4






AGA CAG ACT TTA A





 


AJ_P10
85653678
B05
AJ_881
/5AmMC6/CCC AAA CTG TCT TGT
106535015
8696
59.3






TCG AAC AGC ATA A





 


AJ_P10
85653679
B06
AJ_882
/5AmMC6/CCC AAT TTG TAC ATC
106535016
8687
59.4






GCT TCA TCG GAA A





 


AJ_P10
85653680
B07
AJ_883
/5AmMC6/CCC AAT ACA GAA GGA
106535017
8739
58.9






GTA CCT GAC CTA A





 


AJ_P10
85653681
B08
AJ_884
/5AmMC6/CCC AAT CGC AAA GAA
106535018
8714
59.4






GTA CCA GTT TCA A





 


AJ_P10
85653682
B09
AJ_885
/5AmMC6/CCC AAC TGG TAG ACA
106535019
8779
60.4






TGC ATA GAA GCA A





 


AJ_P10
85653683
B10
AJ_886
/5AmMC6/CCC AAG AGA ACT ACC
106535020
8795
62.2






GTT GTG AAG GCA A





 


AJ_P10
85653684
B11
AJ_887
/5AmMC6/CCC AAT TTC GAG AGT
106535021
8714
58.8






CAC ATC AAC AGA A





 


AJ_P10
85653685
B12
AJ_888
/5AmMC6/CCC AAC GGT AAG GCT
106535022
8712
60.1






ACC TCT TTG TAA A





 


AJ_P10
85653686
C01
AJ_889
/5AmMC6/CCC AAC TAC GCT ACT
106535023
8723
58.5






AAA GTA AAG GCA A





 


AJ_P10
85653687
C02
AJ_890
/5AmMC6/CCC AAC GTG AGT TCG
106535024
8721
60






TTA ACT ACC AGA A





 


AJ_P10
85653688
C03
AJ_891
/5AmMC6/CCC AAT GGT CTA GCA
106535025
8681
60.2






TTC AAC TAC CGA A





 


AJ_P10
85653689
C04
AJ_892
/5AmMC6/CCC AAT GTT TCA GAC
106535026
8672
60






CTG ACT ACC TGA A





 


AJ_P10
85653690
C05
AJ_893
/5AmMC6/CCC AAT AAC AGA ACC
106577190
8699
60.3






CAT GCT CAG GTA A





 


AJ_P10
85653691
C06
AJ_894
/5AmMC6/CCC AAA CAC GTT GCA
106535028
8687
60






CTT TAC TTT GGA A





 


AJ_P10
85653692
C07
AJ_895
/5AmMC6/CCC AAT GCT GAC GTA
106535029
8723
59.3






CAC AAA CAA GTA A





 


AJ_P10
85653693
C08
AJ_896
/5AmMC6/CCC AAA GCT GTT GCT
106535030
8736
59.9






GTT AAA CCG TAA A





 


AJ_P10
85653694
C09
AJ_897
/5AmMC6/CCC AAC ATG TTG TGG
106535031
8761
60.8






TAG CTA CCG AAA A





 


AJ_P10
85653695
C10
AJ_898
/5AmMC6/CCC AAA TCT CTG TGG
106535032
8761
60.2






TAG CAT AAC GGA A





 


AJ_P10
85653696
C11
AJ_899
/5AmMC6/CCC AAG AGC TCT CGT
106535033
8736
57.8






GTT ACT AAA GTA A





 


AJ_P10
85653697
C12
AJ_900
/5AmMC6/CCC AAA GCC TTG GTT
106535034
8727
59.5






GTC AGT CTT AAA A





 


AJ_P10
85653698
D01
AJ_901
/5AmMC6/CCC AAG TAC CTC TAC
106535035
8657
60.2






TCT GAC TCA GGA A





 


AJ_P10
85653699
D02
AJ_902
/5AmMC6/CCC AAG GCA TAC AAC
106535036
8666
61.9






TCT GAC CTG TCA A





 


AJ_P10
85653700
D03
AJ_903
/5AmMC6/CCC AAC CAG TAA ACC
106535037
8675
62.6






AGT GAC TTG CCA A





 


AJ_P10
85653701
D04
AJ_904
/5AmMC6/CCC AAG ACT CCT TGG
106535038
8721
60.6






TTC AAC GGT AAA A





 


AJ_P10
85653702
D05
AJ_905
/5AmMC6/CCC AAC TTA GGT AGG
106535039
8770
59.7






TAG CAC ACT GAA A





 


AJ_P10
85653703
D06
AJ_906
/5AmMC6/CCC AAA GTC CAG AGC
106535040
8714
58.8






ACA TTT CAT AGA A





 


AJ_P10
85653704
D07
AJ_907
/5AmMC6/CCC AAG GCT ACA TGT
106535041
8675
61.6






CAC CTA ACC AGA A





 


AJ_P10
85653705
D08
AJ_908
/5AmMC6/CCC AAT GTC CAT GAC
106535042
8672
60.4






TTT CCT AAC GGA A





 


AJ_P10
85653706
D09
AJ_909
/5AmMC6/CCC AAG CAC ATG GTT
106535043
8699
61.2






CCA CAT AAA CGA A





 


AJ_P10
85653707
D10
AJ_910
/5AmMC6/CCC AAG CCA TGT TGC
106535044
8699
61.4






ACA CTA CAA AGA A





 


AJ_P10
85653708
D11
AJ_911
/5AmMC6/CCC AAA CGC ATC CAA
106535045
8739
60.9






AGT TAG GGT ACA A





 


AJ_P10
85653709
D12
AJ_912
/5AmMC6/CCC AAC CAC TCG TAG
106535046
8706
60.1






TCT ACT AGG AGA A





 


AJ_P10
85653710
E01
AJ_913
/5AmMC6/CCC AAA CTG TGT TGT
106535047
8752
59.8






CTC ACT AGA GGA A





 


AJ_P10
85653711
E02
AJ_914
/5AmMC6/CCC AAG TAC TCC TAC
106535048
8657
61.1






TCG TAC ATG GCA A





 


AJ_P10
85653712
E03
AJ_915
/5AmMC6/CCC AAT AAC ACG AAA
106535049
8714
59.9






GCT TGT GCA TCA A





 


AJ_P10
85653713
E04
AJ_916
/5AmMC6/CCC AAT TTC TAG AAC
106535050
8687
59.6






TGT GCT TGC ACA A





 


AJ_P10
85653714
E05
AJ_917
/5AmMC6/CCC AAG GTG TAC CTT
106535051
8777
61.7






TGA CCA GTG AGA A





 


AJ_P10
85653715
E06
AJ_918
/5AmMC6/CCC AAG TTA CCT CTT
106535052
8681
60.1






GCC ATA CGA GAA A





 


AJ_P10
85653716
E07
AJ_919
/5AmMC6/CCC AAG AAC GTT CTG
106535053
8714
59.6






CTC ATA GCA AAA A





 


AJ_P10
85653717
E08
AJ_920
/5AmMC6/CCC AAA CGC TTC TTC ATT
106535054
8696
59.4






GTA ACA GGA A





 


AJ_P10
85653718
E09
AJ_921
/5AmMC6/CCC AAG AGT CTC GAC
106535055
8657
59.8






TCC TCT ACT AGA A





 


AJ_P10
85653719
E10
AJ_922
/5AmMC6/CCC AAG AGT ACA GAA
106535056
8690
59.8






CCT CAC TTT CGA A





 


AJ_P10
85653720
E11
AJ_923
/5AmMC6/CCC AAG TAC TGC TGA
106535057
8699
60.3






CAC AAC TAA CGA A





 


AJ_P10
85653721
E12
AJ_924
/5AmMC6/CCC AAA GCC TTT GGT
106535058
8761
60.1






AGT CAG ACA GTA A





 


AJ_P10
85653722
F01
AJ_925
/5AmMC6/CCC AAA GGC TAC TCA
106535059
8714
59






GAA CAA CTT TGA A





 


AJ_P10
85653723
F02
AJ_926
/5AmMC6/CCC AAG TAC CTC ACT
106535060
8675
61.6






CAA GCA TCA GGA A





 


AJ_P10
85653724
F03
AJ_927
/5AmMC6/CCC AAA TAG TCT CAG
106535061
8752
60.3






TGT GCT AGT GCA A





 


AJ_P10
85653725
F04
AJ_928
/5AmMC6/CCC AAG TCC ACT TTC
106535062
8697
62






TGC ACT AAG GGA A





 


AJ_P10
85653726
F05
AJ_929
/5AmMC6/CCC AAC AGT GCT TGC
106535063
8723
60.3






AAA CAT CAA AGA A





 


AJ_P10
85653727
F06
AJ_930
/5AmMC6/CCC AAA CTT GTC TCT CTG
106535064
8712
59.5






AGT ACA GGA A





 


AJ_P10
85653728
F07
AJ_931
/5AmMC6/CCC AAA GTT CTC CAC
106535065
8730
60.2






AAG TGT CAG AGA A





 


AJ_P10
85653729
F08
AJ_932
/5AmMC6/CCC AAG TCT TCA CAC
106535066
8690
60.4






TCA GAA CGT GAA A





 


AJ_P10
85653730
F09
AJ_933
/5AmMC6/CCC AAT CCG AAG TTG
106535067
8754
59






CGT AGA CTA AAA A





 


AJ_P10
85653731
F10
AJ_934
/5AmMC6/CCC AAG AAA CAT CGT
106535068
8699
60.1






ACA CAG TCT CGA A





 


AJ_P10
85653732
F11
AJ_935
/5AmMC6/CCC AAG AAC CAT CAC
106535069
8675
62.4






CTG TCA GCA TGA A





 


AJ_P10
85653733
F12
AJ_936
/5AmMC6/CCC AAC GAC ATA CCT
106535070
8739
60.5






AAA GCA TGG TGA A





 


AJ_P10
85653734
G01
AJ_937
/5AmMC6/CCC AAG GTC ACA GCA
106535071
8666
61.9






CTT TCC ACT AGA A





 


AJ_P10
85653735
G02
AJ_938
/5AmMC6/CCC AAC GAG TTA CAC
106535072
8705
59.6






GTT TGC CTA AAA A





 


AJ_P10
85653736
G03
AJ_939
/5AmMC6/CCC AAG TAC GCT AGT
106535073
8681
58.9






CTC TCA CAT AGA A





 


AJ_P10
85653737
G04
AJ_940
/5AmMC6/CCC AAA GTG TCT GAC
106535074
8681
59.9






CAT ACT TAC CGA A





 


AJ_P10
85653738
G05
AJ_941
/5AmMC6/CCC AAC GTT CCA TAC
106535075
8699
60






CAA GGA CAT AGA A





 


AJ_P10
85653739
G06
AJ_942
/5AmMC6/CCC AAG GAC TTC GAC
106535076
8681
59.1






TTC CTA CTA AGA A





 


AJ_P10
85653740
G07
AJ_943
/5AmMC6/CCC AAT GAC GTT GTA
106535077
8681
60.5






AAC CTC TCA CGA A





 


AJ_P10
85653741
G08
AJ_944
/5AmMC6/CCC AAG CAC TGT GTA
106535078
8690
61






AAC AAC CTT CGA A





 


AJ_P10
85653742
G09
AJ_945
/5AmMC6/CCC AAC ATG TAG AGA
106535079
8763
58.1






AAC TCT CGA GAA A





 


AJ_P10
85653743
G10
AJ_946
/5AmMC6/CCC AAC AGC TTC CTC
106535080
8672
59.5






ATA GTC TTA GGA A





 


AJ_P10
85653744
G11
AJ_947
/5AmMC6/CCC AAG TCC TAC ACA
106535081
8675
61.3






CAG TCA TAC GGA A





 


AJ_P10
85653745
G12
AJ_948
/5AmMC6/CCC AAG TCC ATA CAT
106535082
8666
62.3






CCG AAC TGT GCA A





 


AJ_P10
85653746
H01
AJ_949
/5AmMC6/CCC AAG AAC TTC CAC
106535083
8681
61






TTA GCA TGT GCA A





 


AJ_P10
85653747
H02
AJ_950
/5AmMC6/CCC AAG GTT CTA CAT
106535084
8690
60.7






CAC GTA CGC AAA A





 


AJ_P10
85653748
H03
AJ_951
/5AmMC6/CCC AAG AGT GCT ACC
106535085
8730
60






TTC GTA CAG AAA A





 


AJ_P10
85653749
H04
AJ_952
/5AmMC6/CCC AAA TAA GTC CTG
106535086
8763
58.8






AAG GAA CGC ATA A





 


AJ_P10
85653750
H05
AJ_953
/5AmMC6/CCC AAG TGC AAC GAG
106535087
8739
61.4






ACC TTT GAC AAA A





 


AJ_P10
85653751
H06
AJ_954
/5AmMC6/CCC AAG CAC TGT TGA
106535088
8681
61.5






AAC CCT TTC GAA A





 


AJ_P10
85653752
H07
AJ_955
/5AmMC6/CCC AAA CTC GTC ACC
106535089
8681
61






TTT GGG TAA ACA A





 


AJ_P10
85653753
H08
AJ_956
/5AmMC6/CCC AAA GCC TTC TTG
106535090
8721
60.2






GTC ATA GAC AGA A





 


AJ_P10
85653754
H09
AJ_957
/5AmMC6/CCC AAC AAC GGT ACT
106535091
8752
61.1






TTG TTG GTA GCA A





 


AJ_P10
85653755
H10
AJ_958
/5AmMC6/CCC AAC ATT CTG GTG
106535092
8752
60.6






TTA CGA ACT GGA A





 


AJ_P10
85653756
H11
AJ_959
/5AmMC6/CCC AAT GAA ACC ATC
106535093
8699
61






CAT GTC AGA GCA A





 


AJ_P10
85653757
H12
AJ_960
/5AmMC6/CCC AAA ACT GAC CAT
106535094
8761
61.9






TGT GGT GTG CAA A









Example 11
Titration or Dilution Series
The ability to perform multiple experiments in parallel enables straightforward exploration of the counting results from samples with a range of starting concentrations or amounts of target, sometimes known as a titration experiment or a dilution series.
An example of dilution series data for a labeled RPLPO gene sequence is shown in FIG. 26. Plotted in the figure is the counting result N for each array where the nominal starting concentration of mRNA in the reaction is shown on the X axis.
Some of the graphical output from the analysis software for the same experiment is shown in FIG. 27. For each array, there is a compound display with the following elements: (i) an intensity histogram (green) for the index spots, (ii) a blue line registered with the histogram, showing the dynamic threshold for spot counting, (iii) a 32×32 grid which is a digital representation of each array. A white site in the grid denotes a spot whose intensity was above the dynamic threshold, and a black site denotes that the intensity was below the dynamic threshold, and (iv) the result N and the quality score Q is reported for each array as text.
While preferred embodiments of the present invention have been shown and described herein, it will be obvious to those skilled in the art that such embodiments may be provided by way of example only. Numerous variations, changes, and substitutions will now occur to those skilled in the art without departing from the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in practicing the invention.

## Claims

1. An array reader system comprising
a computer system comprising a digital processor configured to execute computer-executable instructions to at least:
(a) acquiring image data of a region of an array, wherein the array comprises a plurality of stochastically labeled and non-labeled features, and wherein the features comprise oligonucleotide probes;
(b) measuring a signal intensity and a local background intensity for one of the plurality of stochastically labeled and non-labeled features based on the acquired image data;
(c) calculating a local background corrected signal intensity for the one of the plurality of stochastically labeled and non-labeled features using the signal intensity and the local background intensity measured in (b);
(d) transforming the local background corrected signal intensity calculated in (c) for the one of the plurality of stochastically labeled and non-labeled features to determine the number of stochastically labeled and non-labeled features in the of the array; and
(e) calculating the absolute number of a target molecule based on the number of stochastically labeled and non-labeled features determined in (d) within the region of the array.

2. The array reader system of claim 1, further comprising an optical imaging system that comprises one or more image sensors and an illumination system, wherein the illumination system comprises at least one light source; and
wherein acquiring the image data of the region of the array comprises acquiring the image data of the region of the array from the optical imaging system.

3. The array reader system of claim 1, wherein the array comprises a microarray, microscope slide, or microwell plate.

4. The array reader system of claim 2, wherein the optical imaging system has a magnification of less than 1, equal to 1, or greater than 1.

5. The array reader system of claim 2, wherein the optical imaging system comprises a fluorescence imaging system.

6. The array reader system of claim 2, wherein the optical imaging system comprises a phosphorescence imaging system.

7. The array reader system of claim 2, wherein the optical imaging system comprises an imaging system that operates in a transmitted light, reflected light, or scattered light imaging mode, or combinations thereof.

8. The array reader system of claim 2, wherein the one or more image sensors have a resolution of at least 320×240 pixels.

9. The array reader system of claim 2, wherein the one or more image sensors are CCD image sensors.

10. The array reader system of claim 2, wherein the one or more image sensors are CMOS Image sensors.

11. The array reader system of claim 2, wherein the one or more image sensors comprise one or more circuit boards.

12. The array reader system of claim 2, wherein the optical imaging system further comprises one or more components selected from the group including, but not limited to, a microscope objective, a camera lens, a finite-conjugate lens, an infinite-conjugate lens, a plano-convex lens, a double convex lens, a plano-concave lens, a double concave lens, an achromatic cemented doublet, or a bandpass filter.

13. The array reader system of claim 5, wherein the fluorescence imaging system is designed for use with fluorescein, Cy3, Cy5, or phycoerythrin fluorophores.

14. The array reader system of claim 2, wherein the at least one light source is an LED or LED assembly.

15. The array reader system of claim 2, wherein the at least one light source is electronically synchronized with the image sensor, the at least one light source being turned on when the image sensor is acquiring an image and turned off when the image sensor is not acquiring an image.

16. The array reader system of claim 2, wherein the illumination system is an off-axis illumination system.

17. The array reader system of claim 16, wherein the off-axis illumination system satisfies the Scheimpflug condition.

18. The array reader system of claim 16, wherein the off-axis illumination system does not satisfy the Scheimpflug condition.

19. The array reader system of claim 16, wherein the off-axis illumination subsystem is a Kohler illumination system.

20. The array reader system of claim 16, wherein the off-axis illumination system is an Abbe illumination system.

21. The array reader system of claim 2, wherein the illumination system is an epi-illumination system.

22. The array reader system of claim 21, wherein the epi-illumination system is a Kohler illumination system.

23. The array reader system of claim 21, wherein the epi-illumination system is an Abbe illumination system.

24. The array reader system of claim 2, wherein the illumination system is a trans-illumination system.

25. The array reader system of claim 24, wherein the trans-illumination system is a Kohler illumination system.

26. The array reader system of claim 24, wherein the trans-illumination system is an Abbe illumination system.

27. The array reader system of claim 2, wherein the optical imaging system further comprises a translation stage.

28. The array reader system of claim 27, wherein the translation stage is a single-axis translation stage.

29. The array reader system of claim 27, wherein the translation stage is a dual-axis translation stage.

30. The array reader system of claim 27, wherein the translation stage is a multi-axis translation stage.

31. The array reader system of claim 1, wherein the digital processor is configured to automatically locates features of the array within the acquired image data.

32. The array reader system of claim 1, wherein calculating the local background corrected signal intensity for the one of the plurality of stochastically labeled and non-labeled features using the signal intensity and the local background intensity measured in (b) comprises:
(i) centering a predefined analysis window on an array feature within an image,
(ii) calculating an intensity value statistic for signal and background pixels according to a predefined pattern of pixels within the array feature, and
(iii) utilizing the intensity value statistic for signal and background pixels to calculate the local background corrected signal intensity for the array feature.

33. The array reader system of claim 32, wherein the digital processor is configured to perform a k-means clustering analysis of the background corrected signal intensity values for the array features to determine a dynamic signal intensity threshold for discrimination between the plurality of stochastically labeled and non-labeled features of the array.

34. The array reader system of claim 32, wherein the digital processor is configured to perform a k-medoids clustering analysis of the background corrected signal intensity values for the array features to determine a dynamic signal intensity threshold for discrimination between the plurality of stochastically labeled and non-labeled features of the array.

35. The array reader system of claim 32, wherein the digital processor is configured to perform a mixture model statistical analysis of the background corrected signal intensity values for the array features to determine a dynamic signal intensity threshold for discrimination between the plurality of stochastically labeled and non-labeled features of the array.

36. The array reader system of claim 32, wherein the digital processor is configured to perform an empirical analysis based on sorting of background corrected signal intensity values for the array features to determine a dynamic signal intensity threshold for discrimination between the plurality of stochastically labeled and non-labeled features of the array.

37. The array reader system of claim 32, wherein the digital processor is configured to perform an empirical analysis based on sorting of pairwise differences in background corrected signal intensity values for the array features to determine a dynamic signal intensity threshold for discrimination between the plurality of stochastically labeled and non-labeled features of the array.

38. The array reader system of claim 32, wherein the digital processor is configured to perform one or more statistical analyses of the background corrected signal intensity values for the array features to determine a dynamic signal intensity threshold for discrimination between the plurality of stochastically labeled and non-labeled features of the array, and wherein the one or more statistical analyses are selected from the list comprising k-means clustering, k-medoids clustering, mixture model statistical analysis, an empirical analysis, or any combination thereof.

39. The array reader system of claim 1, wherein calculating the absolute number of the target molecule based on the number of stochastically labeled and non-labeled features determined in (d) within the region of the array comprises calculate the absolute number of the target molecule based on the number of stochastically labeled features, the number of non-labeled features within the region of the array, and the predictions of the Poisson distribution.

40. The array reader system of claim 1, wherein the digital processor is configured to calculate a confidence interval for the number of target molecules.

41. The array reader system of claim 2, wherein the optical imaging system and computer system are combined within a single, stand-alone instrument.

42. The array reader system of claim 2, wherein the optical imaging system and computer system are configured as separate instrument modules.

43. The array reader system of claim 32, wherein the digital processor is configured to perform an analysis of the local background corrected signal intensities for the array features to determine a dynamic signal intensity threshold, and wherein the analysis comprises fitting a model function to the local background corrected signal intensities by varying model parameters.

44. The array reader system of claim 32, wherein the digital processor is configured to perform an analysis of the local background corrected signal intensities for the array features to determine a dynamic signal intensity threshold, and wherein the analysis comprises maximizing a quality metric relating to a statistical difference between feature intensities above the threshold and feature intensities below the threshold.