RNA-SeQC: RNA-seq metrics for quality control and process optimization
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Abstract
UNLABELLED: RNA-seq, the application of next-generation sequencing to RNA, provides transcriptome-wide characterization of cellular activity. Assessment of sequencing performance and library quality is critical to the interpretation of RNA-seq data, yet few tools exist to address this issue. We introduce RNA-SeQC, a program which provides key measures of data quality. These metrics include yield, alignment and duplication rates; GC bias, rRNA content, regions of alignment (exon, intron and intragenic), continuity of coverage, 3'/5' bias and count of detectable transcripts, among others. The software provides multi-sample evaluation of library construction protocols, input materials and other experimental…
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Topics
Keywords
- Computer science
- RNA-Seq
- RNA
- Data mining
- Software
- Quality (philosophy)
- Pipeline (software)
- Computational biology
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