Support vector machine model of developmental brain gene expression data for prioritization of Autism risk gene candidates.
Journal:
Bioinformatics (Oxford, England)
Published Date:
Aug 9, 2016
Abstract
MOTIVATION: Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders with clinical heterogeneity and a substantial polygenic component. High-throughput methods for ASD risk gene identification produce numerous candidate genes that are time-consuming and expensive to validate. Prioritization methods can identify high-confidence candidates. Previous ASD gene prioritization methods have focused on a priori knowledge, which excludes genes with little functional annotation or no protein product such as long non-coding RNAs (lncRNAs).