Quantitative visualization of alternative exon expression from RNA-seq data

Yarden Katz, Eric T. Wang, Jacob Silterra, Schraga Schwartz, Bang Wong, Helga Thorvaldsdottir, James T. Robinson, Jill P. Mesirov, Edoardo M. Airoldi, Christopher B. Burge

Research output: Contribution to journalArticlepeer-review


Motivation: Analysis of RNA sequencing (RNA-Seq) data revealed that the vast majority of human genes express multiple mRNA isoforms, produced by alternative pre-mRNA splicing and other mechanisms, and that most alternative isoforms vary in expression between human tissues. As RNA-Seq datasets grow in size, it remains challenging to visualize isoform expression across multiple samples. Results: To help address this problem, we present Sashimi plots, a quantitative visualization of aligned RNA-Seq reads that enables quantitative comparison of exon usage across samples or experimental conditions. Sashimi plots can be made using the Broad Integrated Genome Viewer or with a stand-alone command line program.

Original languageEnglish
Pages (from-to)2400-2402
Number of pages3
Issue number14
StatePublished - 15 Jul 2015

All Science Journal Classification (ASJC) codes

  • Computational Mathematics
  • Molecular Biology
  • Biochemistry
  • Statistics and Probability
  • Computer Science Applications
  • Computational Theory and Mathematics


Dive into the research topics of 'Quantitative visualization of alternative exon expression from RNA-seq data'. Together they form a unique fingerprint.

Cite this