A benchmark for RNA-seq quantification pipelines. Academic Article uri icon

Overview

abstract

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

publication date

  • April 23, 2016

Research

keywords

  • Algorithms
  • Sequence Analysis, RNA

Identity

PubMed Central ID

  • PMC4842274

Scopus Document Identifier

  • 84989332129

Digital Object Identifier (DOI)

  • 10.1093/biostatistics/4.2.249

PubMed ID

  • 27107712

Additional Document Info

volume

  • 17