Document Type

Article

Publication Date

2014

Department

Mathematics, Statistics, and Computer Science

Keywords

way analysis, whole-genome sequence, hypertension, family studies, Genetic Analysis Workshop 18

Abstract

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

Comments

This is a pre-publication author manuscript of the final, published article. The definitive version is published by Wiley and available from Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/gepi.21831

Source Publication Title

Genetic Epidemiology

Publisher

WIley

Volume

38

Issue

S1

First Page

S86

DOI

10.1002/gepi.21831

Download

Share

COinS