META-GSA: Combining Findings from Gene-Set Analyses across Several Genome-Wide Association Studies

Authors

Albert Rosenberger, Georg-August University
Stefanie Friedrichs, Georg-August University
Christopher I. Amos, Dartmouth CollegeFollow
Paul Brennan, International Agency for Research on Cancer (IARC), Lyon, FranceFollow
Gordon Fehringer, Prosserman Centre for Health Research
Joachim Heinrich, German Research Center for Environmental Health, Neuherberg, Germany
Rayjean J. Hung, Prosserman Centre for Health Research
Thomas Muley, Translational Lung Research Center Heidelberg (TLRC-H)
Martina Müller-Nurasyid, Ludwig-Maximilians-University Munich
Angela Risch, Translational Lung Research Center Heidelberg (TLRC-H)
Heike Bickeböller, Georg-August University GöttingenFollow

Document Type

Article

Publication Date

10-26-2015

Publication Title

PloS One

Department

Geisel School of Medicine

Abstract

Gene-set analysis (GSA) methods are used as complementary approaches to genome-wide association studies (GWASs). The single marker association estimates of a predefined set of genes are either contrasted with those of all remaining genes or with a null non-associated background. To pool the p-values from several GSAs, it is important to take into account the concordance of the observed patterns resulting from single marker association point estimates across any given gene set. Here we propose an enhanced version of Fisher’s inverse χ²-method META-GSA, however weighting each study to account for imperfect correlation between association patterns.

DOI

10.1371/journal.pone.0140179

Dartmouth Digital Commons Citation

Rosenberger, Albert; Friedrichs, Stefanie; Amos, Christopher I.; Brennan, Paul; Fehringer, Gordon; Heinrich, Joachim; Hung, Rayjean J.; Muley, Thomas; Müller-Nurasyid, Martina; Risch, Angela; and Bickeböller, Heike, "META-GSA: Combining Findings from Gene-Set Analyses across Several Genome-Wide Association Studies" (2015). Dartmouth Scholarship. 2917.
https://digitalcommons.dartmouth.edu/facoa/2917