Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics.

Details

Ressource 1Download: BIB_50526236BCA7.P001.pdf (1455.52 [Ko])
State: Public
Version: Final published version
Serval ID
serval:BIB_50526236BCA7
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics.
Journal
Plos Computational Biology
Author(s)
Lamparter D., Marbach D., Rueedi R., Kutalik Z., Bergmann S.
ISSN
1553-7358 (Electronic)
ISSN-L
1553-734X
Publication state
Published
Issued date
2016
Volume
12
Number
1
Pages
e1004714
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: epublish
Abstract
Integrating single nucleotide polymorphism (SNP) p-values from genome-wide association studies (GWAS) across genes and pathways is a strategy to improve statistical power and gain biological insight. Here, we present Pascal (Pathway scoring algorithm), a powerful tool for computing gene and pathway scores from SNP-phenotype association summary statistics. For gene score computation, we implemented analytic and efficient numerical solutions to calculate test statistics. We examined in particular the sum and the maximum of chi-squared statistics, which measure the strongest and the average association signals per gene, respectively. For pathway scoring, we use a modified Fisher method, which offers not only significant power improvement over more traditional enrichment strategies, but also eliminates the problem of arbitrary threshold selection inherent in any binary membership based pathway enrichment approach. We demonstrate the marked increase in power by analyzing summary statistics from dozens of large meta-studies for various traits. Our extensive testing indicates that our method not only excels in rigorous type I error control, but also results in more biologically meaningful discoveries.
Keywords
Algorithms, Computational Biology/methods, Genome-Wide Association Study/methods, HapMap Project, Humans, Phenotype, Polymorphism, Single Nucleotide/genetics, Software
Pubmed
Web of science
Open Access
Yes
Create date
11/02/2016 16:32
Last modification date
20/08/2019 14:06
Usage data