Improved detection of rare genetic variants for diseases.

ABSTRACT: Technology advances have promoted gene-based sequencing studies with the aim of identifying rare mutations responsible for complex diseases. A complication in these types of association studies is that the vast majority of non-synonymous mutations are believed to be neutral to phenotypes. It is thus critical to distinguish potential causative variants from neutral variation before performing association tests. In this study, we used existing predicting algorithms to predict functional amino acid substitutions, and incorporated that information into association tests. Using simulations, we comprehensively studied the effects of several influential factors, including the sensitivity and specificity of functional variant predictions, number of variants, and proportion of causative variants, o

SUBMITTER: Zhang L 

PROVIDER: S-EPMC2975623 | biostudies-literature | 2010 Nov

REPOSITORIES: biostudies-literature