cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/100237
title: NeuroView: a customizable browser-base utility

description: The amount of data acquired for an fMRI experiment dimension wise is very large and a challenge for neuroscience studies, in particular for data analysis and visualization. Diverse tools have been developed to confront these challenges, but their analytical results can differ. Addressing those differences is not facilitated by existing tools. The goal of this Brainhack project was to build a flexible utility to analyze fMRI experimental results. This utility is called NeuroView. NeuroView allows researchers to extend the visualizations to their context: every visual behavior or interactions of this tool is customizable. We implemented NeuroView to work in Web-browsers, using JavaScript and the libraries D3.js and jQuery.<br>We create three tools using NeuroView to best analyze our research results: CC200 search, SVM coefficients and Connectivity matrix.<br>This is an initial version of a browser-based neuroimage viewer. The main focus is to develop an embeddable viewer, instead of a standalone desktop software. By doing so, research results can be presented on interactive views, enriching their analysis and interpretation. In our case study, NeuroView facilitates quick evaluation of features for machine learning algorithms, and promotes discussion about them, since the results will inform researchers about their data.<br>In future work, we aim to directly load Nifti images at client-side and support some AFNI features, such as voxel clustering.
DOI: 10.5524/100238
title: DIPY: Brain tissue classification

description: To implement an image segmentation algorithm in DIPY for classifying the different tissue types of the brain using structural T1 images and diffusion MRI images (dMRI) as well as to incorporate tissue probability maps for Anatomically constrained tractography (ACT). DMRI is used for creating visual representations of the structural connectivity of the brain, also known as tractography. Research has shown that using a tissue classifier can be of great benefit to create more accurate representations of the underlying connections.<br>We used a Bayesian approach for the segmentation by applying the Maximum-A-Posteriori (MAP) procedure. The prior probability was modeled with Markov Random Fields (MRF). The MRF distribution was modeled as a Gibbs distribution. We used the Expectation Maximization (EM) algorithm to update the tissue labels at each site and to update the parameters of the log-likelihood in all iterations.<br>We developed a segmentation algorithm based on a Bayesian framework by using the MAP-MRF approach and EM. The algorithm was tested on T1-weighted images as well as on dMRI derived maps, such as the Diffusion Power Maps (DPM) The tissue specific probability maps from both the T1 and the DPMs were then used for ACT.
DOI: 10.5524/100242
title: Supporting data for "The Whole Genome Sequences and Experimentally Phased Haplotypes of over 100 Personal Genomes"

description: Since the completion of the Human Genome Project in 2003 it has been estimated that over 200,000 individual whole human genomes have been sequenced; a stunning accomplishment in such a short period of time. However, most of these were sequenced without experimental haplotype data and as such are missing an important aspect of genome biology. In addition, much of the genomic data generated is not available to the public and lacks phenotypic information.<br>As part of the Personal Genome Project (PGP), 184 participants blood samples were collected and processed with Complete Genomics Long Fragment Read (LFR) technology. Here we report the results for the experimental whole genome haplotyping and sequencing of these samples to an average read coverage depth of 100X of 114 of these samples. This level of coverage is approximately 3 fold higher than the read coverage applied to most whole human genome assemblies and was done to ensure the highest quality results. Currently only 114 genomes from this data set are freely available on GigaDB and are associated with rich phenotypic data provided in this manuscript. It is our expectation that all 184 participants genomes will be made freely available in the near future, as soon as the individuals concerned have reviewed their own genomes prior to release in accordance with the PGP agreement. <br>Twenty genomes were sequenced at least two times using independently made LFR barcoded libraries for reproducibility analyses. Additionally, 7 genomes were also sequenced using Complete Genomics standard non-barcoded library process. <br>These genomes represent a unique source of haplotype and phenotype data for the scientific community. In addition, we report 2.6 million high quality rare variants not previously identified in dbSNP or Phase 3 1000 Genomes Project (1KG) data. The data presented here should help expand our understanding of the human genome evolution and functioning.<br><br><br>PLEASE NOTE: The files associated with this dataset are hosted in cold storage, please contact us via email with the details of the dataset and any particular files you would like to download, and we will be happy to make those available to you.<br>
DOI: 10.5524/100246
title: Supporting data for "Draft genome of the leopard gecko, Eublepharis macularius"

description: Geckos are among the most species-rich reptile groups and the sister clade to all other lizards and snakes. Geckos possess a suite of distinctive characteristics, including: adhesive digits; nocturnal activity; hard, calcareous eggshells; and lack of eyelids. However, one gecko clade, the Eublepharidae, seems to be the exception to most of these rules and lack adhesive toe pads, have eyelids, and lay eggs with soft, leathery eggshells. These differences make eublepharids an important component of any investigation into the underlying genomic innovations contributing to the distinctive phenotypes in typical geckos.<br>
We report the high-depth genome sequencing, assembly, and annotation for a male leopard gecko, Eublepharis macularius (Eublepharidae). Illumina sequence data were generated from seven insert libraries (ranging from 170 bp to 20 kb), representing a raw sequencing depth of 136X from 303 GB of data; reduced to 84X and 187 Gb after filtering. The assembled genome size was 2.02 Gb, close to the 2.23 Gb estimated by k-mer analysis. Scaffold and contig N50 sizes were 664 kb and 20 kb, respectively, comparable to the previously published Gekko japonicus genome. Repetitive elements made up 42% of the genome. Gene annotation yielded 24,755 protein-coding genes, of which 93% were functionally annotated. CEGMA and BUSCO assessment showed that our assembly captured 91% (225 of 248) of eukaryotic core genes and 76% of the vertebrate universal single-copy orthologs.<br>
The leopard gecko genome assembly provides a valuable resource for future comparative genomic studies of geckos and other squamate reptiles.
DOI: 10.5524/100248
title: Supporting data for "Comparative optical genome analysis of two Pangolin species Manis pentadactyla and Manis javanica"

description: The pangolin is a Pholidota mammal with large keratin scales protecting its skin. Two pangolin species (Manis pentadactyla and Manis javanica) have been recorded as critically endangered on the International Union for Conservation of Nature Red List of Threatened Species. Optical mapping constructs high-resolution restriction maps from a single-strand DNA molecule for genome analysis at the mega-base scale and to assist genome assembly. Here, we constructed restriction maps of M. pentadactyla and M. javanica using optical mapping to assist with genome assembly and analysis of these species.<br>
 Genomic DNA was nicked with Nt.BspQI, followed by labeling using fluorescent-labeled bases that were detected by the Irys optical mapping system. In total, 3,313,734 DNA molecules (517.847 Gb) for M. pentadactyla and 3,439,885 DNA molecules (504.743 Gb) for M. javanica were obtained, which corresponded to approximately 178X and 177X genome coverage, respectively. Qualified molecules (150 Kb with a label density of &gt; 6 sites/100 kilobases) were analyzed using the de novo assembly program embedded in the IrysView pipeline. We obtained two maps that were 2.91 Gb and 2.85 Gb in size with N50s of 1.88 Mb and 1.97 Mb, respectively. <br>
Optical mapping reveals large-scale structural information that is especially important for non-model genomes that lack a good reference. The approach has the potential to guide NGS-based de novo assembly. Our data provide a resource for Manidae genome analysis and references for de novo assembly.
DOI: 10.5524/100249
title: Supporting data for "The genome of Antarctic-endemic Copepod, Tigriopus kingsejongensis"

description: The Antarctic intertidal zone is continuously subject to extreme fluctuations in biotic and abiotic stressors, and the West Antarctic Peninsula is the most rapidly warming region on earth. Organisms living in Antarctic intertidal pools are therefore of great interest for research on topics such as evolutionary adaptation to extreme environments and the effects of climate change.<br> 
Here, we report the whole-genome sequence of the Antarctic endemic Harpacticoid copepod, Tigriopus kingsejongensis with a total of 37 Gb raw DNA sequence using Illumina Miseq platform and the libraries were prepared with 65-fold coverage with a total length of 295 Mb. The final assembly consists of 48,368 contigs with an N50 contig length of 17.5 kb and 27,823 scaffolds with N50 contig length of 159.2 kb and a total of 12,772 coding genes were inferred using the MAKER annotation pipeline approach. Comparative genome analysis revealed that T. kingsejongensis specific genes are enriched in transport and metabolism processes. Furthermore, rapidly evolving genes related to energy metabolism showed signatures of positive selection.<br>
The genome of T. kingsejongensis will provide an interesting example of an evolutionary strategy for Antarctic cold adaptation, and offers new genetic insights into Antarctic intertidal biota.
DOI: 10.5524/100251
title: Supporting data for "Morphometric analysis of Passiflora leaves: the relationship between landmarks of the vasculature and elliptical Fourier descriptors of the blade"

description: Leaf shape among Passiflora species is spectacularly diverse. Underlying this diversity in leaf shape are profound changes in the patterning of the primary vasculature and laminar outgrowth. Each of these aspects of leaf morphologyvasculature and bladeprovides different insights into leaf patterning.<br>
Here, we morphometrically analyze &gt;3,300 leaves from 40 different Passiflora species collected sequentially across the vine. Each leaf is measured in two different ways: using 1) 15 homologous Procrustes-adjusted landmarks of the vasculature, sinuses, and lobes and 2) Elliptical Fourier Descriptors (EFDs), which quantify the outline of the leaf. The ability of landmarks, EFDs, and both datasets together are compared to determine their relative ability to predict species and node position within the vine. Pairwise correlation of x and y landmark coordinates and EFD harmonic coefficients reveals close associations between traits and insights into the relationship between vasculature and blade patterning.<br>
Landmarks, more reflective of the vasculature, and EFDs, more reflective of the blade contour, describe both similar and distinct features of leaf morphology. Landmarks and EFDs vary in ability to predict species identity and node position in the vine and exhibit a correlational structure (both within landmark or EFD traits and between the two data types) revealing constraints between vascular and blade patterning underlying natural variation in leaf morphology among Passiflora species.
DOI: 10.5524/100252
title: BGISEQ-500 sequencer first reference dataset

description: BGISEQ-500 sequencer is a new desktop sequencer developed by BGI. Using DNA nanoballs (DNB) and combinational probe-anchor synthesis (cPAS) developed from Complete Genomics(TM) sequencing technology, it generates short reads at a large scale, which can help fulfill the growing demands for sequencing. 
Here, we present the first human whole genome sequencing dataset from the BGISEQ-500. The dataset was generated by sequencing the widely used Genome in a Bottle Consortium cell line, HG001 (NA12878) in one sequencing run. And the sequencing data were ~1,000 million paired sequences with the length of 50 bp (PE50). We also include examples of the raw images from the sequencer for reference. Finally, we carried out variation calling based on the dataset and compared it that identified from similar amount of publicly available HiSeq2500 data and the previously identified high confident variations.
DOI: 10.5524/100253
title: Supporting data for "Shotgun Metagenomics of 250 Adult Twins Reveals Genetic and Environmental Impacts on the Gut Microbiome"

description: The first large cohort of shotgun sequenced dataset for the gut microbiome in twins, including 250 adult twins in the TwinsUK registry, leading to an updated reference gene catalog of 11.4 million genes. Heritability was identified in microbial taxa and potential functions, and sharing of microbial single-nucleotide polymorphisms (SNPs) between twins were demonstrated, all underscoring the value of twins for the understanding of the genetic and environmental underpinnings of the gut microbiome.
DOI: 10.5524/100257
title: Supporting data for "Draft genome of the sea cucumber Apostichopus japonicus and genetic polymorphism among color variants"

description: The Japanese sea cucumber (<em>Apostichopus japonicus</em> Selenka 1867) is an economically important species as a source of seafood and ingredient in traditional medicine. It is mainly found off the coasts of northeast Asia. Recently, substantial exploitation and widespread biotic disease have generated increasing conservation concern. <br>
Here we present a total of 312 gigabases (Gb) of raw sequences were generated using the Illumina HiSeq 2000 platform and assembled to a final size of 0.66 Gb which is about 80.5 % of the estimated genome size (0.82 Gb). We observed nucleotide-level heterozygosity within the assembled genome to be 0.986 %. The resulting draft genome assembly comprising 132,607 scaffolds with an N50 value of 10.5 kb contains a total of 21,771 predicted protein-coding genes. We identified 6.6 14.5 million heterozygous SNPs in the assembled genome of the three natural color variants (green, red, and black), resulting in an estimated nucleotide diversity of 0.00146.
DOI: 10.5524/100258
title: Supporting data for "De novo transcriptome assemblies of four xylem sap-feeding insects"

description: The four xylem-feeding insects are all vectors of the pytopahogenic bacterium that causes Pierce's disease of grapevines and other crop diseases. Here we have sequenced, <em>de novo</em> assembled, and annotated a comprehensive transcriptome from these four insects. These four transcriptomes represent a significant expansion of data for insect herbivores that feed exclusively on xylem sap, a nutritionally deficient dietary source relative to other plant tissues and fluids. Comparison of transcriptome data with insect herbivores that utilize other dietary sources may illuminate fundamental differences in the biochemistry of dietary specialization.
DOI: 10.5524/100210
title: Supporting data for "Chromosomer: a reference-based genome arrangement tool for producing draft chromosome sequences"

description: As the number of sequenced genomes rapidly increases, chromosome assembly is becoming an even more crucial step of any genome study. Since de novo chromosome assemblies are confounded by repeat-mediated artifacts, reference-assisted assemblies that use comparative inference have become widely used, prompting the development of several reference-assisted assembly programs for prokaryotic and eukaryotic genomes.<br>
We developed Chromosomer - a reference-based genome arrangement tool, which rapidly builds chromosomes from genome contigs or scaffolds using their alignments to a reference genome of a closely related species. Chromosomer does not require mate-pair libraries and it offers a number of auxiliary tools that implement common operations accompanying the genome assembly process.<br>
Despite implementing a straightforward alignment-based approach, Chromosomer is a useful tool for genomic analysis of species without chromosome maps. Putative chromosome assemblies by Chromosomer can be used in comparative genomic analysis, genomic variation assessment, potential linkage group inference and other kinds of analysis involving contig or scaffold mapping to a high-quality assembly.<br>
DOI: 10.5524/100218
title: Integrating the Brain Imaging Data Structure (BIDS) standard into C-PAC

description: Data acquired during neuroimaging experiments can be organized in many ways. This stems from differences in scanner software, various DICOM and NIFTI tools, and custom data organizing scripts within different laboratories. The Brain Imaging Data Structure (BIDS) specification provides a simple, straightforward solution to this problem by introducing an intuitive standard for neuroimaging data organization. The widespread adoption of BIDS can be facilitated through incorporating this standard into software projects used for neuroimaging analysis. These software packages will in turn benefit from the homogenous data structure and ease of specifying data acquisition parameters afforded by BIDS. The goal of this Brainhack project was to integrate BIDS into the Configurable Pipeline for the Analysis of Connectomes (C-PAC) a python software built on Nipype for the high-throughput analysis of resting state fMRI data. <br>The updated C-PAC GUI reflects the BIDS and Custom options, with the Custom option allowing users to specify their data structure as in previous versions of C-PAC. In the future this option would be more elegantly displayed via a radio button with the input fields dynamically changing to reflect the type of input desired. <br>Incorporating the BIDS subject list builder into C-PAC is a great step forward in bringing the standard to a broader audience. Throughout the integration process, other technologies were discovered that could further enable input data gathering across a wide range of file system types, including FTP, SFTP, Zip, S3, and an array of virtual filesystems. With further development, the overhead of preprocessing ones own neuroimaging data for discovery science can be minimized so scientists can focus on the results.
DOI: 10.5524/100219
title: Optimized implementations of voxel-wise degree centrality and local functional connectivity density mapping in AFNI

description: Degree centrality (DC) and local functional connectivity density (lFCD) are statistics calculated from brain connectivity graphs that measure how important a brain region is to the graph. DC (a.k.a. global functional connectivity density) is calculated as the number of connections a region has with the rest of the brain (binary DC), or the sum of weights for those connections (weighted DC). lFCD was developed to be a surrogate measure of DC that is faster to calculate by restricting its computation to regions that are spatially adjacent. Although both of these measures are popular for investigating inter-individual variation in brain connectivity, efficient neuroimaging tools for computing them are scarce. The goal of this Brainhack project was to contribute optimized implementations of these algorithms to the widely used, open source, AFNI software package. <br>Tools for calculating DC (3dDegreeCentrality) and lFCD (3dLFCD) were implemented by modifying the C source code of AFNIs 3dAutoTcorrelate tool. 3dAutoTcorrelate calculates the voxel voxel correlation matrix for a dataset and includes most of the functionality we require, including support for OpenMP multithreading to improve calculation time, the ability to restrict the calculation using a user-supplied or auto-calculated mask, and support for both Pearsons and Spearman correlation. <br>Outputs from the newly developed tools were benchmarked to Python implementations of these measures from the Configurable Pipeline for the Analysis of Connectomes (C-PAC) using the publically shared Intrinsic Brain Activity Test-Retest (IBATRT) dataset from the Consortium for Reliability and Reproducibility.
DOI: 10.5524/100223
title: Human Connectome Project Minimal Preprocessing Pipelines to Nipype

description: The goal was to convert the Human Connectome Project (HCP) Minimal Preprocessing Pipelines into Nipype code. The HCP minimal preprocessing pipelines represent a significant advance in image processing pipelines in our time. They provide preprocessed volume and surface data in native and atlas space, for both functional and structural data. Nipype is an open source neuroimaging project for designing imaging pipelines which has been around since 2011 and provides many excellent features for provenance and reliability of processing pipelines. Together, these two pieces of software would allow for a more robust, more flexible synergy of pipeline design and operability. <br>More work is needed to truly contribute back to the HCP Pipelines. The greatest achievement of the hackathon project was forming a collaborative team of interested Nipype developers who were trained and are ready to continue collaborating across seven institutions. Future work will continue trying to achieve the original goals as stated, but may need an organizer to hold the team accountable to deadlines.
DOI: 10.5524/100227
title: DueCredit: automated collection of citations for software, methods, and data

description: Data analysis software and canonical datasets are the driving force behind many fields of empirical sciences. Despite being of paramount importance, those resources are most often not adequately cited. Although some can consider this a social problem, its roots are technical: Users of those resources often are simply not aware of the underlying computational libraries and methods they have been using in their research projects. This in-turn fosters inefficient practices that encourage the development of new projects, instead of contributing to existing established ones. Some projects (e.g. FSL) facilitate citation of the utilized methods, but such efforts are not uniform, and the output is rarely in commonly used citation formats (e.g. BibTeX). DueCredit is a simple framework to embed information about publications or other references within the original code or dataset descriptors. References are automatically reported to the user whenever a given functionality or dataset is being used.<br>DueCredit is currently available for Python, but we envision extending support to other frameworks (e.g., Matlab, R). Until DueCredit gets adopted natively by the projects, it provides the functionality to inject references for 3rd party modules.<br>For the developer, DueCredit implements a decorator @due.dcite that allows to link a method or class to a set of references that can be specified through a doi or BibTeX entry. <br>The initial release of DueCredit (0.1.0) was implemented during the OHBM 2015 hackathon and uploaded to pypi and is freely available. DueCredit provides a concise API to associate a publication reference with any given module or function. DueCredit comes with a simple demo code, which demonstrates its utility. <br>DueCredit is in its early stages of development, but two days of team development at the OHBM hackathon were sufficient to establish a usable prototype implementation. Since then, the code-base was further improved and multiple beta-releases followed, expanding the coverage of citable resources (e.g., within scipy, sklearn modules via injections and PyMVPA natively).