A benchmark for RNA-seq quantification pipelines

• DOI: 10.1186/s13059-016-0940-1
• Publication Date: 2016-04-23T12:40:26Z
• Authors: Mingxiang Teng; Michael I. Love; Carrie A. Davis; Sarah Djebali; Alexander Dobin; Brenton R. Graveley; Sheng Li; Christopher E. Mason; Sara Olson; Dmitri Pervouchine; Cricket A. Sloan; Xintao Wei; Lijun Zhan; Rafael A. Irizarry
• Keywords: Bioconductor; Benchmark (surveying); R package

Obtaining RNA-seq measurements involves a complex data analytical process with large number of competing algorithms as options. There is much debate about which these methods provides the best approach. Unfortunately, it currently difficult to evaluate their performance due in part lack sensitive assessment metrics. We present series statistical summaries and plots terms specificity sensitivity, available R/Bioconductor package ( http://bioconductor.org/packages/rnaseqcomp ). Using two independent datasets, we assessed seven pipelines. Performance was generally poor, clearly underperforming RSEM slightly outperforming rest.