Pathway Analysis Approaches for Rare and Common Variants: Insights From Genetic Analysis Workshop 18

摘要: Pathway analysis, broadly defined as a group of methods incorporating priori biological information from public databases, has emerged promising approach for analyzing high-dimensional genomic data. As part Genetic Analysis Workshop 18, seven research groups applied pathway analysis techniques to whole-genome sequence data the San Antonio Family Study. Overall, found that potential improve detection causal variants by lowering multiple-testing burden and biologic insight remains largely unrealized. Specifically, there is lack best practices at each stage approach: annotation, interpretation, follow-up. Annotation genetic inconsistent across incomplete, biased toward known genes. At insufficient statistical power major challenge. Analyses combining rare common may have an inflated type I error rate not Inclusion genes power, although fraction explained phenotypic variance be more appropriate metric. Interpretation findings further complicated evidence in support interactions between pathways consensus on how incorporate functional information. Finally, all presented approaches warranted follow-up studies, both reduce likelihood false-positive identify specific within given pathway. Despite initial promise modeling complexity disease phenotypes, many methodological challenges currently remain addressed.