Analysing high-throughput sequencing data in Python with HTSeq 2.0

Abstract Summary HTSeq 2.0 provides a more extensive application programming interface including a new representation for sparse genomic data, enhancements for htseq-count to suit single-cell omics, a new script for data using cell and molecular barcodes, improved documentation, testing and deployme...

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Bibliographic Details
Published in:Bioinformatics Vol. 38; no. 10; pp. 2943 - 2945
Main Authors: Putri, Givanna H, Anders, Simon, Pyl, Paul Theodor, Pimanda, John E, Zanini, Fabio
Format: Journal Article
Language:English
Published: England Oxford University Press 15.05.2022
Subjects:
Bioinformatics and Computational Biology
Bioinformatik och beräkningsbiologi
Biologi
Biological Sciences
Natural Sciences
Naturvetenskap
ISSN:1367-4803, 1367-4811, 1460-2059, 1367-4811
Online Access:Get full text
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Summary:Abstract Summary HTSeq 2.0 provides a more extensive application programming interface including a new representation for sparse genomic data, enhancements for htseq-count to suit single-cell omics, a new script for data using cell and molecular barcodes, improved documentation, testing and deployment, bug fixes and Python 3 support. Availability and implementation HTSeq 2.0 is released as an open-source software under the GNU General Public License and is available from the Python Package Index at https://pypi.python.org/pypi/HTSeq. The source code is available on Github at https://github.com/htseq/htseq. Supplementary information Supplementary data are available at Bioinformatics online.
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ISSN:1367-4803
1367-4811
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btac166