Identifying rare-variant associations in parent-child trios using a Gaussian support vector machine.

ABSTRACT: As the availability of cost-effective high-throughput sequencing technology increases, genetic research is beginning to focus on identifying the contributions of rare variants (RVs) to complex traits. Using RVs to detect associated genes requires statistical approaches that mitigate the lack of power with the analysis of single RVs. Here we report the development and application of an approach that aggregates and evaluates the transmissions of RVs in parent-child trios. An initial score that incorporates the distortion in transmission of the observed RVs from the parents to their offspring is calculated for each variant. The scores are analyzed using a support vector machine that handles these data by mapping the transmission distortion of the multiple RVs into a one-dimensional score in a

SUBMITTER: Lu AT 

PROVIDER: S-EPMC4143758 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature