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Bioinformatics. 2015 Jul 15;31(14):2400-2. doi: 10.1093/bioinformatics/btv034. Epub 2015 Jan 22.

Quantitative visualization of alternative exon expression from RNA-seq data.

Author information

1
Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, Department of Biology, MIT, Cambridge, MA.
2
Department of Biology, MIT, Cambridge, MA.
3
The Broad Institute of Harvard, MIT, Cambridge, MA, USA.
4
The Broad Institute of Harvard, MIT, Cambridge, MA, USA, Department of Statistics, Harvard University, Cambridge, MA, USA and.
5
Department of Biology, MIT, Cambridge, MA, Department of Biological Engineering, MIT, Cambridge, MA.

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.

AVAILABILITY AND IMPLEMENTATION:

Software code and documentation freely available here: http://miso.readthedocs.org/en/fastmiso/sashimi.html

PMID:
25617416
PMCID:
PMC4542614
DOI:
10.1093/bioinformatics/btv034
[Indexed for MEDLINE]
Free PMC Article

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