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PMID: 21478487 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't

Comrad: detection of expressed rearrangements by integrated analysis of RNA-Seq and low coverage genome sequence data.

Bioinformatics (Oxford, England) ·Vol. 27 ·No. 11 ·2011-06-01 ·Pages 1481-8

McPherson A, Wu C, Hajirasouliha I, Hormozdiari F, Hach F, Lapuk A, Volik S, Shah S, Collins C, Sahinalp SC

Abstract

Comrad is a novel algorithmic framework for the integrated analysis of RNA-Seq and whole genome shotgun sequencing (WGSS) data for the purposes of discovering genomic rearrangements and aberrant transcripts. The Comrad framework leverages the advantages of both RNA-Seq and WGSS data, providing accurate classification of rearrangements as expressed or not expressed and accurate classification of the genomic or non-genomic origin of aberrant transcripts. A major benefit of Comrad is its ability to accurately identify aberrant transcripts and associated rearrangements using low coverage genome data. As a result, a Comrad analysis can be performed at a cost comparable to that of two RNA-Seq experiments, significantly lower than an analysis requiring high coverage genome data. We have applied Comrad to the discovery of gene fusions and read-throughs in prostate cancer cell line C4-2, a derivative of the LNCaP cell line with androgen-independent characteristics. As a proof of concept, we have rediscovered in the C4-2 data 4 of the 6 fusions previously identified in LNCaP. We also identified six novel fusion transcripts and associated genomic breakpoints, and verified their existence in LNCaP, suggesting that Comrad may be more sensitive than previous methods that have been applied to fusion discovery in LNCaP. We show that many of the gene fusions discovered using Comrad would be difficult to identify using currently available techniques. A C++ and Perl implementation of the method demonstrated in this article is available at http://compbio.cs.sfu.ca/.

MeSH Terms
Algorithms Cell Line, Tumor Chromosome Breakpoints Chromosome Mapping Gene Expression Profiling Gene Fusion Genomics/methods Humans Mutant Chimeric Proteins/genetics,metabolism RNA Splicing RNA, Messenger/metabolism Sequence Analysis, DNA/methods Sequence Analysis, RNA/methods
Chemicals
Mutant Chimeric Proteins RNA, Messenger
Authors & Affiliations
10 authors, click to expand affiliations / ORCID
McPherson Andrew
School of Computing Science, Simon Fraser University, Burnaby, BC V5A 1S6, Canada. [email protected]
Wu Chunxiao
Hajirasouliha Iman
Hormozdiari Fereydoun
Hach Faraz
Lapuk Anna
Volik Stanislav
Shah Sohrab
Collins Colin
Sahinalp S Cenk
Article Info
Journal
Bioinformatics (Oxford, England)
Abbr.
Bioinformatics
ISSN
1367-4811
Published
2011-06-01
Epub
2011-00-09
Pages
1481-8
Language
English
Region
England
NLM ID
9808944
Subset
IM
Grants
Canadian Institutes of Health Research · Canada
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