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Old 04-12-2011, 02:40 AM   #1
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Default RNA-Seq: Comrad: a novel algorithmic framework for the integrated analysis of RNA-Seq

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Comrad: a novel algorithmic framework for the integrated analysis of RNA-Seq and WGSS data.

Bioinformatics. 2011 Apr 9;

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

MOTIVATION: 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. RESULTS: 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 6 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. AVAILABILITY: A C++ and Perl implementation of the method demonstrated in this paper is available at http://compbio.cs.sfu.ca/ CONTACT: andrew.mcpherson@gmail.com.

PMID: 21478487 [PubMed - as supplied by publisher]



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