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Hum Hered. 2012;73(2):63-72. doi: 10.1159/000336196. Epub 2012 Mar 7.

Integrated genome-wide pathway association analysis with INTERSNP.

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  • 1German Center for Neurodegenerative Diseases (DZNE), University of Bonn, Bonn, Germany.

Abstract

OBJECTIVES:

Pathway association analysis (PAA) tests for an excess of moderately significant SNPs in genes from a common pathway.

METHODS:

We present a Monte-Carlo simulation framework that allows to formulate the main ideas of existing PAA approaches using a self-contained rather than a competitive null hypothesis. A stand-alone implementation in INTERSNP makes time-consuming communication with standard GWAS software redundant. By additional parallelization with the OpenMP API, we achieve a reduction in running time for PAA by orders of magnitude, making a power simulation study for PAA feasible. Our approach properly accounts for linkage disequilibrium and is robust with respect to residual λ inflation.

RESULTS:

We demonstrate that under simple, realistic disease models, PAA can actually strongly outperform the GWAS single-marker approach. PAA methods that make use of the strength of the SNP association (GenGen, Fisher's combination test), in general, perform better than ratio-based methods (ALIGATOR, SNP ratio), whereas the relative performance of gene-based scoring (ALIGATOR, GenGen) and pathway-based scoring (SNP ratio, Fisher's combination test) depends on the architecture of the assumed disease model. Finally, we present a new PAA score that models independent signals from the same gene in a regression framework and show that it is a reasonable compromise that combines the advantages of existing ideas.

Copyright © 2012 S. Karger AG, Basel.

PMID:
22399020
[PubMed - indexed for MEDLINE]
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