English

Analysing high-throughput sequencing data in Python with HTSeq 2.0

Genomics 2021-12-03 v1 Quantitative Methods

Abstract

Summary: HTSeq 2.0 provides a more extensive API including a new representation for sparse genomic data, enhancements in 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 Licence and 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. Contact: fabio.zanini@unsw.edu.au

Keywords

Cite

@article{arxiv.2112.00939,
  title  = {Analysing high-throughput sequencing data in Python with HTSeq 2.0},
  author = {Givanna H Putri and Simon Anders and Paul Theodor Pyl and John E Pimanda and Fabio Zanini},
  journal= {arXiv preprint arXiv:2112.00939},
  year   = {2021}
}

Comments

5 pages, 1 figure

R2 v1 2026-06-24T08:00:49.148Z