Near-optimal probabilistic RNA-seq quantification

  • Nat Biotechnol. 2016 May;34(5):525-7. doi: 10.1038/nbt.3519.
Nicolas L Bray  1 ,  Harold Pimentel  2 ,  Páll Melsted  3 ,  Lior Pachter  2  4  5
Affiliations
  • 1. Innovative Genomics Initiative, University of California, Berkeley, California, USA.
  • 2. Department of Computer Science, University of California, Berkeley, California, USA.
  • 3. Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, University of Iceland, Reykjavik, Iceland.
  • 4. Department of Mathematics, University of California, Berkeley, California, USA.
  • 5. Department of Molecular &Cell Biology, University of California, Berkeley, California, USA.
PMID: 27043002 DOI: 10.1038/nbt.3519
Abstract

We present kallisto, an RNA-seq quantification program that is two orders of magnitude faster than previous approaches and achieves similar accuracy. Kallisto pseudoaligns reads to a reference, producing a list of transcripts that are compatible with each read while avoiding alignment of individual Bases. We use kallisto to analyze 30 million unaligned paired-end RNA-seq reads in <10 min on a standard laptop computer. This removes a major computational bottleneck in RNA-seq analysis.