eXtasy: variant prioritization by genomic data fusion
- 29 September 2013
- journal article
- research article
- Published by Springer Science and Business Media LLC in Nature Methods
- Vol. 10 (11), 1083-1084
- https://doi.org/10.1038/nmeth.2656
Abstract
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 (nSNSNVs) that substantially improves prediction of disease-causing variants in exome sequencing data by integrating variant impact prediction, haploinsufficiency prediction and phenotype-specific gene prioritization.Keywords
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