PhenoRank: reducing study bias in gene prioritization through simulation.

ABSTRACT:

Motivation

Genome-wide association studies have identified thousands of loci associated with human disease, but identifying the causal genes at these loci is often difficult. Several methods prioritize genes most likely to be disease causing through the integration of biological data, including protein-protein interaction and phenotypic data. Data availability is not the same for all genes however, potentially influencing the performance of these methods.

Results

We demonstrate that whilst disease genes tend to be associated with greater numbers of data, this may be at least partially a result of them being better studied. With this observation we develop PhenoRank, which prioritizes disease genes whilst avoiding being biased towards genes with more available data. Bias is a

SUBMITTER: Cornish AJ 

PROVIDER: S-EPMC5949213 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature