A Bayesian framework to integrate multi-level genome-scale data for Autism risk gene prioritization.

ABSTRACT:

Background

Autism spectrum disorder (ASD) is a group of complex neurodevelopment disorders with a strong genetic basis. Large scale sequencing studies have identified over one hundred ASD risk genes. Nevertheless, the vast majority of ASD risk genes remain to be discovered, as it is estimated that more than 1000 genes are likely to be involved in ASD risk. Prioritization of risk genes is an effective strategy to increase the power of identifying novel risk genes in genetics studies of ASD. As ASD risk genes are likely to exhibit distinct properties from multiple angles, we reason that integrating multiple levels of genomic data is a powerful approach to pinpoint genuine ASD risk genes.

Results

We present BNScore, a Bayesian model selection framework to probabilistically prio

SUBMITTER: Ji Y 

PROVIDER: S-EPMC9034518 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature