Comparison of automated candidate gene prediction systems using genes implicated in type 2 diabetes by genome-wide association studies.

ABSTRACT:

Background

Automated candidate gene prediction systems allow geneticists to hone in on disease genes more rapidly by identifying the most probable candidate genes linked to the disease phenotypes under investigation. Here we assessed the ability of eight different candidate gene prediction systems to predict disease genes in intervals previously associated with type 2 diabetes by benchmarking their performance against genes implicated by recent genome-wide association studies.

Results

Using a search space of 9556 genes, all but one of the systems pruned the genome in favour of genes associated with moderate to highly significant SNPs. Of the 11 genes associated with highly significant SNPs identified by the genome-wide association studies, eight were flagged as likely candid

SUBMITTER: Teber ET 

PROVIDER: S-EPMC2648789 | biostudies-literature | 2009 Jan

REPOSITORIES: biostudies-literature