Back to Search
Start Over
RNA-SeQC 2: efficient RNA-seq quality control and quantification for large cohorts.
- Source :
- Bioinformatics; Sep2021, Vol. 37 Issue 18, p3048-3050, 3p
- Publication Year :
- 2021
-
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. Code and data for reproducing the figures in this paper are available at https://github.com/getzlab/rnaseqc2-paper. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13674803
- Volume :
- 37
- Issue :
- 18
- Database :
- Complementary Index
- Journal :
- Bioinformatics
- Publication Type :
- Academic Journal
- Accession number :
- 152770352
- Full Text :
- https://doi.org/10.1093/bioinformatics/btab135