Work

Analysing high-throughput sequencing data in Python with HTSeq 2.0

Year: 2022

Type: article

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.

Source: Bioinformatics

DOI: 10.1093/bioinformatics/btac166

Authors: Givanna H Putri, Simon Anders, Paul Theodor Pyl, John E Pimanda, Fabio Zanini

Institutions: UNSW Sydney, Heidelberg University, Lund University, Prince of Wales Hospital

Language: English

Topic: Genomics and Phylogenetic Studies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: hybrid

Estimated APC paid: $3,618

Funders: Medical Research Council, National Health and Medical Research Council