TY  - JOUR
A1  - Backes, Christina
A1  - Rühle, Frank
A1  - Stoll, Monika
A1  - Haas, Jan
A1  - Frese, Karen
A1  - Franke, Andre
A1  - Lieb, Wolfgang
A1  - Wichmann, H.-Erich
A1  - Weis, Tanja
A1  - Kloos, Wanda
A1  - Lenhof, Hans-Peter
A1  - Meese, Eckart
A1  - Katus, Hugo
A1  - Meder, Benjamin
A1  - Keller, Andreas
SP  - 1
TI  - Systematic permutation testing in GWAS pathway analyses: identification of genetic networks in dilated cardiomyopathy and ulcerative colitis
Y1  - 2014///
SN  - 1471-2164
PB  - BioMed Central
ID  - heidok19434
VL  - 15
IS  - 622
AV  - public
EP  - 15
CY  - London
JF  - BMC Genomics
N2  - Background: Genome wide association studies (GWAS) are applied to identify genetic loci, which are associated with complex traits and human diseases. Analogous to the evolution of gene expression analyses, pathway analyses have emerged as important tools to uncover functional networks of genome-wide association data. Usually, pathway analyses combine statistical methods with a priori available biological knowledge. To determine significance thresholds for associated pathways, correction for multiple testing and over-representation permutation testing is applied.   Results: We systematically investigated the impact of three different permutation test approaches for over-representation analysis to detect false positive pathway candidates and evaluate them on genome-wide association data of Dilated Cardiomyopathy (DCM) and Ulcerative Colitis (UC). Our results provide evidence that the gold standard - permuting the case?control status ? effectively improves specificity of GWAS pathway analysis. Although permutation of SNPs does not maintain linkage disequilibrium (LD), these permutations represent an alternative for GWAS data when case?control permutations are not possible. Gene permutations, however, did not add significantly to the specificity. Finally, we provide estimates on the required number of permutations for the investigated approaches.   Conclusions: To discover potential false positive functional pathway candidates and to support the results from standard statistical tests such as the Hypergeometric test, permutation tests of case control data should be carried out. The most reasonable alternative was case?control permutation, if this is not possible, SNP permutations may be carried out. Our study also demonstrates that significance values converge rapidly with an increasing number of permutations. By applying the described statistical framework we were able to discover axon guidance, focal adhesion and calcium signaling as important DCM-related pathways and Intestinal immune network for IgA production as most significant UC pathway.  
UR  - https://archiv.ub.uni-heidelberg.de/volltextserver/19434/
ER  -