Salmon provides fast and bias-aware quantification of transcript expression

Nat Methods. 2017 Apr;14(4):417-419. doi: 10.1038/nmeth.4197. Epub 2017 Mar 6.

Abstract

We introduce Salmon, a lightweight method for quantifying transcript abundance from RNA-seq reads. Salmon combines a new dual-phase parallel inference algorithm and feature-rich bias models with an ultra-fast read mapping procedure. It is the first transcriptome-wide quantifier to correct for fragment GC-content bias, which, as we demonstrate here, substantially improves the accuracy of abundance estimates and the sensitivity of subsequent differential expression analysis.

MeSH terms

  • Algorithms*
  • Base Composition
  • Bayes Theorem
  • Gene Expression Profiling / methods
  • Gene Expression Profiling / statistics & numerical data
  • Sequence Analysis, RNA / methods*
  • Sequence Analysis, RNA / statistics & numerical data