Methods for fine-mapping with chromatin and expression data.

ABSTRACT: Recent studies have identified thousands of regions in the genome associated with chromatin modifications, which may in turn be affecting gene expression. Existing works have used heuristic methods to investigate the relationships between genome, epigenome, and gene expression, but, to our knowledge, none have explicitly modeled the chain of causality whereby genetic variants impact chromatin, which impacts gene expression. In this work we introduce a new hierarchical fine-mapping framework that integrates information across all three levels of data to better identify the causal variant and chromatin mark that are concordantly influencing gene expression. In simulations we show that our method is more accurate than existing approaches at identifying the causal mark influencing expression.

SUBMITTER: Roytman M 

PROVIDER: S-EPMC5843356 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature