Cited by 21,464Genomics and Phylogenetic StudiesSingle-cell and spatial transcriptomicsGene expression and cancer classification

The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.

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

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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@fs.tum.de

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Metadata

Authors
Anders, S., Pyl, P. T., & Huber, W.
Affiliations
European Molecular Biology Laboratory (DE)
Corresponding author
Anders, Simon
Venue
Bioinformatics
Published
2014-09-25
Volume
31
Issue
2
Pages
166-169
ISSN
  • 1367-4803 (ISSN-L)
  • 1367-4811
OpenAlex
W2134526812
Cited by
21,464
References
18
Citations by year
2026: 1267 · 2025: 1823 · 2024: 2188 · 2023: 2215 · 2022: 2453 · 2021: 2749 · 2020: 2323 · 2019: 1943 · 2018: 1658 · 2017: 1272 · 2016: 901 · 2015: 516 · 2014: 134
FWCI
383.82
Type
journal article
Language
en
Open access
Locations
  • Bioinformatics (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
European Commission (305626)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
Keywords
HTSeq, high-throughput sequencing data, Python library, RNA-seq, read counting, differential expression analysis, variant calls, gene models
MeSH terms
Gene Expression Regulation, Humans, Software, Genome, Human, Genomics, High-Throughput Nucleotide Sequencing

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