2013
DOI: 10.1093/nar/gkt214
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The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote

Abstract: Read alignment is an ongoing challenge for the analysis of data from sequencing technologies. This article proposes an elegantly simple multi-seed strategy, called seed-and-vote, for mapping reads to a reference genome. The new strategy chooses the mapped genomic location for the read directly from the seeds. It uses a relatively large number of short seeds (called subreads) extracted from each read and allows all the seeds to vote on the optimal location. When the read length is <160 bp, overlapping subreads … Show more

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Cited by 2,352 publications
(1,771 citation statements)
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“…RNA-seq Reads were aligned to the GRCm38/mm10 build of the Mus musculus genome using the Subread aligner. 50 Only uniquely mapped reads were retained. Genewise counts were obtained using featureCounts.…”
Section: Methodsmentioning
confidence: 99%
“…RNA-seq Reads were aligned to the GRCm38/mm10 build of the Mus musculus genome using the Subread aligner. 50 Only uniquely mapped reads were retained. Genewise counts were obtained using featureCounts.…”
Section: Methodsmentioning
confidence: 99%
“…Sequencing reads were mapped against the Arabidopsis genome (TAIR version 10) using the subread software and default parameter (Liao et al, 2013), and sorted and indexed using the samtools software (Li et al, 2009). All subsequent analyses were performed in the statistical software R (R Core Team, 2015) and software packages implemented in the Bioconductor project (Gentleman et al, 2004).…”
Section: Analyses Of Rna-seq Datasetmentioning
confidence: 99%
“…Between 12 and 190 million reads were analyzed per sample. Reads were aligned to the NCBI37/mm9 build of the Mus musculus genome using the Subread aligner (31). Genewise counts were obtained using featureCounts (32), and log2-reads per kilobase per million reads were averaged over replicates using voom (33).…”
Section: Irf4mentioning
confidence: 99%