Friday, November 22, 2013

Fwd: eXtasy: variant prioritization by genomic data fusion

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eXtasy: variant prioritization by genomic data fusion: "

Nature Methods 10, 1083 (2013).

Authors: Alejandro Sifrim, Dusan Popovic, Leon-Charles Tranchevent, Amin Ardeshirdavani, Ryo Sakai, Peter Konings, Joris R Vermeesch, Jan Aerts, Bart De Moor & Yves Moreau

Massively parallel sequencing greatly facilitates the discovery of novel disease genes causing Mendelian and oligogenic disorders. However, many mutations are present in any individual genome, and identifying which ones are disease causing remains a largely open problem. We introduce eXtasy, an approach to prioritize nonsynonymous single-nucleotide variants (nSNVs) that substantially improves prediction of disease-causing variants in exome sequencing data by integrating variant impact prediction, haploinsufficiency prediction and phenotype-specific gene prioritization.


(Via Nature Methods current.)