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

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      * , ,
      Bioinformatics
      Oxford University Press

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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@ 123456fs.tum.de

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

          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.
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            Cython: The Best of Both Worlds

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              SWIG: An easy to use tool for integrating scripting languages with C and C++

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                Author and article information

                Journal
                Bioinformatics
                Bioinformatics
                bioinformatics
                bioinfo
                Bioinformatics
                Oxford University Press
                1367-4803
                1367-4811
                15 January 2015
                25 September 2014
                25 September 2014
                : 31
                : 2
                : 166-169
                Affiliations
                Genome Biology Unit, European Molecular Biology Laboratory, 69111 Heidelberg, Germany
                Author notes
                *To whom correspondence should be addressed.

                Associate Editor: Michael Brudno

                Article
                btu638
                10.1093/bioinformatics/btu638
                4287950
                25260700
                be4d554c-c520-4c54-8fd2-43255f903061
                © The Author 2014. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 27 February 2014
                : 18 August 2014
                : 21 September 2014
                Page count
                Pages: 4
                Categories
                Original Papers
                Genome Analysis

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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