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GATES: a rapid and powerful gene-based association test using extended Simes procedure.

Abstract：

:The gene has been proposed as an attractive unit of analysis for association studies, but a simple yet valid, powerful, and sufficiently fast method of evaluating the statistical significance of all genes in large, genome-wide datasets has been lacking. Here we propose the use of an extended Simes test that integrates functional information and association evidence to combine the p values of the single nucleotide polymorphisms within a gene to obtain an overall p value for the association of the entire gene. Our computer simulations demonstrate that this test is more powerful than the SNP-based test, offers effective control of the type 1 error rate regardless of gene size and linkage-disequilibrium pattern among markers, and does not need permutation or simulation to evaluate empirical significance. Its statistical power in simulated data is at least comparable, and often superior, to that of several alternative gene-based tests. When applied to real genome-wide association study (GWAS) datasets on Crohn disease, the test detected more significant genes than SNP-based tests and alternative gene-based tests. The proposed test, implemented in an open-source package, has the potential to identify additional novel disease-susceptibility genes for complex diseases from large GWAS datasets.

journal_name

Am J Hum Genet

journal_title

American journal of human genetics

authors

Li MX,Gui HS,Kwan JS,Sham PC

doi

10.1016/j.ajhg.2011.01.019

subject

Has Abstract

pub_date

2011-03-11 00:00:00

pages

283-93

issue

3

eissn

0002-9297

issn

1537-6605

pii

S0002-9297(11)00049-8

journal_volume

88

pub_type

杂志文章

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