Functional Validation of Candidate Genes Detected by Genomic Feature Models.

ABSTRACT: Understanding the genetic underpinnings of complex traits requires knowledge of the genetic variants that contribute to phenotypic variability. Reliable statistical approaches are needed to obtain such knowledge. In genome-wide association studies, variants are tested for association with trait variability to pinpoint loci that contribute to the quantitative trait. Because stringent genome-wide significance thresholds are applied to control the false positive rate, many true causal variants can remain undetected. To ameliorate this problem, many alternative approaches have been developed, such as genomic feature models (GFM). The GFM approach tests for association of set of genomic markers, and predicts genomic values from genomic data utilizing prior biological knowledge. We investigated

SUBMITTER: Rohde PD 

PROVIDER: S-EPMC5940157 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature