Sequence analysis Filtering error from SOLiD Output

Summary: Here, we report the development of a filtering framework designed for efficient identification of both polyclonal and independent errors within SOLiD sequence data. The filtering utilizes the quality values reported by SOLiD’s primary analysis for the identification of the two different types of errors. The filtering framework facilitates the passage of high-quality data into a variety of functional genomics applications, including de novo assemblers and sequence matching programs for SNP calling, improving the output quality and reducing resources necessary for analysis. Availability: This error analysis framework is written in Perl and runs on Mac OS and Linux/Unix systems. The filter, documentation and sample Excel files for quality analysis are available at http://hts.rutgers. edu/filter and are distributed as Open Source software under the GPLv3.0. Contact: tmichael@waksman.rutgers. edu Supplementary information: Supplementary data is available at Bioinformatics online. Received on November 12, 2009; revised on January 31, 2010; accepted on February 1, 2010 High-throughput sequencing (HTS) technologies are revolutionizing biological research by their ability to generate millions of short read sequences in a relatively short time frame. Not only do these platforms expand our knowledge by their ability to sequence genomes, they also expand studies in the related fields of transcriptome and proteome research (Ondov and Varadarajan et al., 2008; Pettersson and Lundeberg et al., 2009). One of the most recent HTS platforms comes from Applied Biosystems (ABI, now Life Technologies, Foster City, CA, USA), the Sequence by Oligonucleotide Ligation and Detection (SOLiD) HTS platform (http://solid.appliedbiosystems.com). This system uses a ligationmediated sequencing strategy that is less prone to some of the problems associated with the polymerase-based sequencing platforms. Unlike other platforms, SOLiD data are collected using colorspace, a representation of two-base encoding, thus requiring a conversion step to attain DNA sequence (Supplement of McKernan and Peckham et al., 2009). This two base encoding requires dual interrogation of each base during SOLiD’s sequencing process aiding in distinguishing sequencing errors from true polymorphisms (McKernan and Peckham et al., 2009; Smith and Quinlan et al., 2008; Valouev and Ichikawa et al., 2008). The SOLiD platform outputs two types of files after primary analysis: a sequence file in colorspace and a quality file containing the corresponding ∗To whom correspondence should be addressed. quality values (QVs). The QVs are calculated by training the sequencing process parameters (image intensity, a noise to signal value and angle) against several annotated datasets. The QVs exhibit a linear relationship between observed and predicted phred-scale quality scores (Hyland and Wessel et al., 2009). In essence, the QVs represent the probability of the color call being inaccurate, i.e. the higher the QV the higher the confidence in the color call’s accuracy. In contrast to other HTS platforms, the SOLiD platform does not prefilter low-quality reads. Therefore, all reads where the two-base transition can be identified, even if with poor quality, are reported after primary analysis. This becomes a crucial problem when dealing with de novo assembly of short read sequences since their assembly is highly sensitive to sequencing errors. Therefore, it becomes critical to mitigate these errors prior to assembly. There are two types of sequencing errors commonly observed, polyclonal/correlated errors and independent, erroneous color calls (Valouev and Ichikawa et al., 2008). Polyclonal and correlated errors occur when the entire read is of poor quality or missequenced due to a bead level problem such as in a polyclonal bead or poor resolution of a particular bead. A polyclonal bead occurs when two different templates are amplified on a single bead and then sequenced, resulting in a hybrid sequence that has no match in the true genome. While the original goal was to identify polyclonal beads, there is no guarantee that all the reads identified by this part of the filter are due to polyclonality. A more robust filtering system using the information gathered during the sequencing run, image intensity, noise to signal and angle, could be designed to distinguish between polyclonal beads versus other types of correlated errors. Single color call errors are independent and can occur multiple times in the sequence also leading to an inaccurate sequence. Here, we present a filtering framework that attempts to optimize the preprocessing step by identification and removal of error prone reads for the SOLiD platform using the QVs provided from the SOLiD’s primary analysis. This algorithm flexibly targets the two different types of errors that can occur during SOLiD sequencing. The goal of the preprocessor is to eliminate the low-quality reads and pass only the high-quality data into downstream applications, saving both resources and improving final output quality. To identify sequencing reads with either polyclonal calls or miscalls, we utilized several resequencing datasets where few mismatches were expected between the reference sequence and the sequencing reads. Using these datasets, profiles for both polyclonal/correlated errors and erroneous color calls were determined through various QV analyses. Using the SOLiD mapping pipeline, the reads were matched to the reference sequence, and similar to other HTS platforms, the number of errors increased © The Author 2010. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org 849 Copyedited by: EC MANUSCRIPT CATEGORY: APPLICATIONS NOTE [15:35 19/2/2010 Bioinformatics-btq045.tex] Page: 850 849–850 A.Sasson et al.