Author:

Keywords:

STADIUS, Science & Technology, Life Sciences & Biomedicine, Biochemical Research Methods, Biochemistry & Molecular Biology, Databases, Genetic, Genetic Predisposition to Disease, Genome, Human, Humans, Mutation, Phenotype, Polymorphism, Single Nucleotide, 06 Biological Sciences, 10 Technology, 11 Medical and Health Sciences, Developmental Biology, 31 Biological sciences

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 (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.