Publication | Open Access
featureCounts: an efficient general-purpose read summarization program
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2013
Year
EngineeringGeneticsEntity SummarizationRead SummarizationGenomicsHigh Throughput SequencingText MiningAutomatic SummarizationNatural Language ProcessingInformation RetrievalData ScienceMolecular EcologyMachine TranslationGene-level SummarizationKnowledge DiscoveryComputer ScienceBioinformaticsFunctional GenomicsMulti-modal SummarizationBiologyLong-read SequencingRead Summarization ProgramNext-generation SequencingComputational BiologyGenome SequencingSystems BiologyMedicineSequence Assembly
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. 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. featureCounts is available under GNU General Public License as part of the Subread (this http URL) or Rsubread (this http URL) software packages.