2014
DOI: 10.1186/1471-2105-15-182
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Skewer: a fast and accurate adapter trimmer for next-generation sequencing paired-end reads

Abstract: BackgroundAdapter trimming is a prerequisite step for analyzing next-generation sequencing (NGS) data when the reads are longer than the target DNA/RNA fragments. Although typically used in small RNA sequencing, adapter trimming is also used widely in other applications, such as genome DNA sequencing and transcriptome RNA/cDNA sequencing, where fragments shorter than a read are sometimes obtained because of the limitations of NGS protocols. For the newly emerged Nextera long mate-pair (LMP) protocol, junction … Show more

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Cited by 1,294 publications
(956 citation statements)
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“…We refer to A. niger gene IDs based on the most up-to-date and accurate annotation of the A. niger NRRL3 genome (http://genome.fungalgenomics.ca/). The RNA-seq reads were cleaned by correcting sequencing errors with Rcorrector (Song and Florea 2015), trimming sequencing adapters and low quality sequences with Skewer (Jiang et al 2014), and removing ribosomal RNA with SortMeRNA (Kopylova et al 2012). The cleaned reads were mapped to NRRL3 transcripts and counted with Salmon (Patro et al 2016), and the read counts were analyzed for differences in transcript expression between genotypes with DESeq2 (Love et al 2014).…”
Section: Transcriptome Analysismentioning
confidence: 99%
“…We refer to A. niger gene IDs based on the most up-to-date and accurate annotation of the A. niger NRRL3 genome (http://genome.fungalgenomics.ca/). The RNA-seq reads were cleaned by correcting sequencing errors with Rcorrector (Song and Florea 2015), trimming sequencing adapters and low quality sequences with Skewer (Jiang et al 2014), and removing ribosomal RNA with SortMeRNA (Kopylova et al 2012). The cleaned reads were mapped to NRRL3 transcripts and counted with Salmon (Patro et al 2016), and the read counts were analyzed for differences in transcript expression between genotypes with DESeq2 (Love et al 2014).…”
Section: Transcriptome Analysismentioning
confidence: 99%
“…We trimmed reads for adapter sequences using the software skewer (v0.1.120) (Jiang et al, 2014). Reads were then quality-filtered using SHORE (v0.9.0) (Ossowski et al, 2008), and reads trimmed to <30 bp due to low quality were discarded.…”
Section: Chip-seq and Peak Callingmentioning
confidence: 99%
“…Passed data sets were quality trimmed using skewer (version 0.1.67; -Q 30; -q 30; -l 75; -m pe) (Jiang et al 2014) The transcriptome was assembled using Trinity (release 2013-02-16; -jaccard_clip; -min_kmer_cov 2; -path_reinforcement_distance 75) (Grabherr et al 2011). The assembly was screened for artificial fusion events caused by low-complexity regions or highly similar UTRs.…”
Section: Data Preparation and Transcriptome Assemblymentioning
confidence: 99%