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Bioinformatics DOI:10.1093/bioinformatics/btab135

RNA-SeQC 2: Efficient RNA-seq quality control and quantification for large cohorts.

Publication TypeJournal Article
Year of Publication2021
AuthorsGraubert, A, Aguet, F, Ravi, A, Ardlie, KG, Getz, G
JournalBioinformatics
Date Published2021 Mar 02
ISSN1367-4811
Abstract

SUMMARY: Post-sequencing quality control is a crucial component of RNA sequencing (RNA-seq) data generation and analysis, as sample quality can be affected by sample storage, extraction, and sequencing protocols. RNA-seq is increasingly applied to cohorts ranging from hundreds to tens of thousands of samples in size, but existing tools do not readily scale to these sizes, and were not designed for a wide range of sample types and qualities. Here, we describe RNA-SeQC 2, an efficient reimplementation of RNA-SeQC (DeLuca et al., 2012) that adds multiple metrics designed to characterize sample quality across a wide range of RNA-seq protocols.

AVAILABILITY AND IMPLEMENTATION: The command-line tool, documentation, and C ++ source code are available at the GitHub repository https://github.com/getzlab/rnaseqc.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DOI10.1093/bioinformatics/btab135
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/33677499?dopt=Abstract

Alternate JournalBioinformatics
PubMed ID33677499