RSeQC

Quality control of RNA-seq experiments

Liguo Wang, Shengqin Wang, Wei Li

Research output: Contribution to journalArticle

494 Citations (Scopus)

Abstract

Motivation: RNA-seq has been extensively used for transcriptome study. Quality control (QC) is critical to ensure that RNA-seq data are of high quality and suitable for subsequent analyses. However, QC is a time-consuming and complex task, due to the massive size and versatile nature of RNA-seq data. Therefore, a convenient and comprehensive QC tool to assess RNA-seq quality is sorely needed.Results: We developed the RSeQC package to comprehensively evaluate different aspects of RNA-seq experiments, such as sequence quality, GC bias, polymerase chain reaction bias, nucleotide composition bias, sequencing depth, strand specificity, coverage uniformity and read distribution over the genome structure. RSeQC takes both SAM and BAM files as input, which can be produced by most RNA-seq mapping tools as well as BED files, which are widely used for gene models. Most modules in RSeQC take advantage of R scripts for visualization, and they are notably efficient in dealing with large BAM/SAM files containing hundreds of millions of alignments.

Original languageEnglish (US)
Article numberbts356
Pages (from-to)2184-2185
Number of pages2
JournalBioinformatics
Volume28
Issue number16
DOIs
StatePublished - Aug 1 2012
Externally publishedYes

Fingerprint

Quality Control
RNA
Quality control
Experiment
Polymerase Chain Reaction
Experiments
Uniformity
Sequencing
Specificity
Genome
Alignment
Coverage
Visualization
Genes
Gene
Module
Evaluate
Polymerase chain reaction
Nucleotides
Transcriptome

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

Cite this

RSeQC : Quality control of RNA-seq experiments. / Wang, Liguo; Wang, Shengqin; Li, Wei.

In: Bioinformatics, Vol. 28, No. 16, bts356, 01.08.2012, p. 2184-2185.

Research output: Contribution to journalArticle

Wang, Liguo ; Wang, Shengqin ; Li, Wei. / RSeQC : Quality control of RNA-seq experiments. In: Bioinformatics. 2012 ; Vol. 28, No. 16. pp. 2184-2185.
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