HTSeq--a Python framework to work with high-throughput sequencing data

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Abstract

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. Contact: sanders@fs.tum.de

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Pybedtools: a flexible Python library for manipulating genomic datasets and annotations

Ryan Dale, Brent S. Pedersen, Aaron Quinlan (2011)

Summary: pybedtools is a flexible Python software library for manipulating and exploring genomic datasets in many common formats. It provides an intuitive Python interface that extends upon the popular BEDTools genome arithmetic tools. The library is well documented and efficient, and allows researchers to quickly develop simple, yet powerful scripts that enable complex genomic analyses. Availability: pybedtools is maintained under the GPL license. Stable versions of pybedtools as well as documentation are available on the Python Package Index at http://pypi.python.org/pypi/pybedtools. Contact: dalerr@niddk.nih.gov; arq5x@virginia.edu Supplementary Information: Supplementary data are available at Bioinformatics online.