Identifying Crohn's disease signal from variome analysis.

ABSTRACT:

Background

After years of concentrated research efforts, the exact cause of Crohn's disease (CD) remains unknown. Its accurate diagnosis, however, helps in management and preventing the onset of disease. Genome-wide association studies have identified 241 CD loci, but these carry small log odds ratios and are thus diagnostically uninformative.

Methods

Here, we describe a machine learning method-AVA,Dx (Analysis of Variation for Association with Disease)-that uses exonic variants from whole exome or genome sequencing data to extract CD signal and predict CD status. Using the person-specific coding variation in genes from a panel of only 111 individuals, we built disease-prediction models informative of previously undiscovered disease genes. By additionally accounting for batc

SUBMITTER: Wang Y 

PROVIDER: S-EPMC6767648 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature