Papers › Analysing high-throughput sequencing data in Python with HTSeq 2.0

Analysing high-throughput sequencing data in Python with HTSeq 2.0

2 Dec 2021arXiv:2112.00939archive 2025-07-28

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

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

PaperPDFCode

Code

htseq/htseq officialmentioned in paper report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

Vocal Bursts Intensity Prediction

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections