Cited by 27,219Genomics and Phylogenetic StudiesGene expression and cancer classificationSingle-cell and spatial transcriptomics

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featureCounts: an efficient general purpose program for assigning sequence reads to genomic features

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Liao, Yang, Smyth, Gordon K., Shi, Wei·2014·Bioinformatics

DOI 10.1093/bioinformatics/btt656

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Abstract

MOTIVATION: Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. RESULTS: We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. AVAILABILITY AND IMPLEMENTATION: featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.

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Self-citation

Authors: Liao, Y., Smyth, G. K., & Shi, W.
Affiliations: The University of Melbourne (AU)
Corresponding author: Shi, Wei
ORCID: Liao, Yang
Smyth, Gordon K.
Shi, Wei
Venue: Bioinformatics
Publisher: Oxford University Press (OUP)
Published: 2013-11-13
Volume: 30
Issue: 7
Pages: 923-930
ISSN: 1367-4803 (ISSN-L)
1367-4811
DOI: 10.1093/bioinformatics/btt656
OpenAlex: W2138207763
Cited by: 27,219
References: 47
Citations by year: 2026: 3661 · 2025: 4344 · 2024: 4323 · 2023: 3554 · 2022: 3316 · 2021: 2761 · 2020: 2083 · 2019: 1326 · 2018: 894 · 2017: 561 · 2016: 250 · 2015: 99 · 2014: 31 · 2013: 6
FWCI: 58.18
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: Bioinformatics (publishedVersion)
PubMed (publishedVersion)
arXiv (Cornell University) (submittedVersion)
arXiv (Cornell University)
Funders: Australian Government
Medical Research Council
National Health and Medical Research Council (1023454)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords: featureCounts, read counting, genomic features, paired-end reads, RNA-seq
MeSH terms: Algorithms, Histones, Software, Genome, Sequence Analysis, RNA, Genomics, High-Throughput Nucleotide Sequencing

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featureCounts: an efficient general purpose program for assigning sequence reads to genomic features

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