eXtasy: variant prioritization by genomic data fusion.
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.
1] Department of Electrical Engineering, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium. [2] iMinds Future Health Department, Leuven, Belgium. [3].
Alejandro
A
Sifrim
Dusan
D
Popovic
Leon-Charles
LC
Tranchevent
Amin
A
Ardeshirdavani
Ryo
R
Sakai
Peter
P
Konings
Joris R
JR
Vermeesch
Jan
J
Aerts
Bart
B
De Moor
Yves
Y
Moreau
D030541:Databases, Genetic; D020022:Genetic Predisposition to Disease; D015894:Genome, Human; D006801:Humans; D009154:Mutation; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide