Fcfdr: an R package to leverage continuous and binary functional genomic data in GWAS.

ABSTRACT:

Background

Genome-wide association studies (GWAS) are limited in power to detect associations that exceed the stringent genome-wide significance threshold. This limitation can be alleviated by leveraging relevant auxiliary data, such as functional genomic data. Frameworks utilising the conditional false discovery rate have been developed for this purpose, and have been shown to increase power for GWAS discovery whilst controlling the false discovery rate. However, the methods are currently only applicable for continuous auxiliary data and cannot be used to leverage auxiliary data with a binary representation, such as whether SNPs are synonymous or non-synonymous, or whether they reside in regions of the genome with specific activity states.

Results

We describe an extension t

SUBMITTER: Hutchinson A 

PROVIDER: S-EPMC9338519 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature