HTSeq—a Python framework to work with high-throughput sequencing data
HTSeq — фреймворк на Python для работы с данными высокопроизводительного секвенирования
2014-09-25
SCID: 54.1/r9qzy7yg
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HTSeqPython libraryhigh-throughput sequencing (HTS)htseq-count (RNA-Seq read counting for differential expression)parsers for HTS data formats
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Abstract (AI)
MOTIVATION: A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard workflows, custom scripts are needed. RESULTS: We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data, such as genomic coordinates, sequences, sequencing reads, alignments, gene model information and variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. AVAILABILITY AND IMPLEMENTATION: HTSeq is released as an open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index at https://pypi.python.org/pypi/HTSeq.
Key Findings
1
HTSeq includes data structures that support querying by genomic coordinates, enabling coordinate-based analyses within Python scripts.
2
HTSeq is a Python library designed to facilitate rapid development of custom scripts for non-standard high-throughput sequencing (HTS) analysis tasks.
3
HTSeq is released as open-source software under the GNU General Public Licence and is available from the project website and the Python Package Index.
4
HTSeq provides parsers for many common HTS data formats and classes representing genomic coordinates, sequences, reads, alignments, gene models, and variant calls.
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The accompanying tool htseq-count, developed with HTSeq, preprocesses RNA-Seq data for differential expression by counting overlaps of reads with genes.
Research Object
HTSeq Python library for working with high-throughput sequencing (HTS) data
Research Subject
Facilitating rapid development of custom scripts for HTS data analysis by providing parsers for common HTS formats, data-representation classes (genomic coordinates, sequences, reads, alignments, gene models, variant calls), genomic-coordinate-queryable data structures, and an example tool (htseq-count) for counting read–gene overlaps in RNA-Seq preprocessing
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2014-09-25
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