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

featureCounts: эффективная универсальная программа для назначения считываний последовательностей геномным особенностям
Gordon K. Smyth, Wei Shi, Yang Liao
2013-11-13

chromosome hashingfeature blockingfeatureCountsgene-level read countingread summarization
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.
1
featureCounts implements highly efficient chromosome hashing and feature blocking techniques to assign reads to features.
2
featureCounts is a general-purpose read summarization program for counting reads mapping to genomic features from RNA or genomic DNA sequencing.
3
featureCounts is available under the GNU General Public License as part of the Subread and Rsubread software packages.
4
featureCounts is considerably faster than existing methods, achieving about an order of magnitude speedup for gene-level summarization.
5
featureCounts requires far less computer memory than existing read-counting methods.
6
featureCounts supports single- and paired-end reads and provides a wide range of options for different sequencing applications.

featureCounts read summarization program for assigning sequencing reads to genomic features

Efficient and memory‑saving assignment/counting of short sequencing reads (single- or paired-end, RNA or genomic DNA) to genomic features (exons, genes) using chromosome hashing and feature blocking

Publication Details
Publication Date
2013-11-13
Journal
Publisher
ISSN
Access Type
Author Information
Authors
Gordon K. Smyth
Wei Shi
Yang Liao
Explore further
Open the scid.ai AI chat with a ready-made request: it will find papers on a similar topic and help build a literature review.
Find similar papers in the chat
Make a presentation
100%