Ranking non-synonymous single nucleotide polymorphisms based on disease concepts.

ABSTRACT: As the number of non-synonymous single nucleotide polymorphisms (nsSNPs) identified through whole-exome/whole-genome sequencing programs increases, researchers and clinicians are becoming increasingly reliant upon computational prediction algorithms designed to prioritize potential functional variants for further study. A large proportion of existing prediction algorithms are 'disease agnostic' but are nevertheless quite capable of predicting when a mutation is likely to be deleterious. However, most clinical and research applications of these algorithms relate to specific diseases and would therefore benefit from an approach that discriminates between functional variants specifically related to that disease from those which are not. In a whole-exome/whole-genome sequencing context, such a

SUBMITTER: Shihab HA 

PROVIDER: S-EPMC4083756 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature