Quantitative visualization of alternative exon expression from RNA-seq data

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

Research output: Contribution to journalArticle

Abstract

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 (US)
Pages (from-to)2400-2402
Number of pages3
JournalBioinformatics
Volume31
Issue number14
DOIs
StatePublished - 2015
Externally publishedYes

ASJC Scopus subject areas

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

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  • Cite this

    Katz, Y., Wang, E. T., Silterra, J., Schwartz, S., Wong, B., Thorvaldsdóttir, H., Robinson, J. T., Mesirov, J. P., Airoldi, E. M., & Burge, C. B. (2015). Quantitative visualization of alternative exon expression from RNA-seq data. Bioinformatics, 31(14), 2400-2402. https://doi.org/10.1093/bioinformatics/btv034