A comprehensive evaluation of collapsing methods using simulated and real data: excellent annotation of functionality and large sample sizes required.

ABSTRACT: The advent of next generation sequencing (NGS) technologies enabled the investigation of the rare variant-common disease hypothesis in unrelated individuals, even on the genome-wide level. Analysis of this hypothesis requires tailored statistical methods as single marker tests fail on rare variants. An entire class of statistical methods collapses rare variants from a genomic region of interest (ROI), thereby aggregating rare variants. In an extensive simulation study using data from the Genetic Analysis Workshop 17 we compared the performance of 15 collapsing methods by means of a variety of pre-defined ROIs regarding minor allele frequency thresholds and functionality. Findings of the simulation study were additionally confirmed by a real data set investigating the association between me

SUBMITTER: Dering C 

PROVIDER: S-EPMC4164031 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature