Establishing an adjusted p-value threshold to control the family-wide type 1 error in genome wide association studies.

Abstract:

BACKGROUND:By assaying hundreds of thousands of single nucleotide polymorphisms, genome wide association studies (GWAS) allow for a powerful, unbiased review of the entire genome to localize common genetic variants that influence health and disease. Although it is widely recognized that some correction for multiple testing is necessary, in order to control the family-wide Type 1 Error in genetic association studies, it is not clear which method to utilize. One simple approach is to perform a Bonferroni correction using all n single nucleotide polymorphisms (SNPs) across the genome; however this approach is highly conservative and would "overcorrect" for SNPs that are not truly independent. Many SNPs fall within regions of strong linkage disequilibrium (LD) ("blocks") and should not be considered "independent". RESULTS:We proposed to approximate the number of "independent" SNPs by counting 1 SNP per LD block, plus all SNPs outside of blocks (interblock SNPs). We examined the effective number of independent SNPs for Genome Wide Association Study (GWAS) panels. In the CEPH Utah (CEU) population, by considering the interdependence of SNPs, we could reduce the total number of effective tests within the Affymetrix and Illumina SNP panels from 500,000 and 317,000 to 67,000 and 82,000 "independent" SNPs, respectively. For the Affymetrix 500 K and Illumina 317 K GWAS SNP panels we recommend using 10(-5), 10(-7) and 10(-8) and for the Phase II HapMap CEPH Utah and Yoruba populations we recommend using 10(-6), 10(-7) and 10(-9) as "suggestive", "significant" and "highly significant" p-value thresholds to properly control the family-wide Type 1 error. CONCLUSION:By approximating the effective number of independent SNPs across the genome we are able to 'correct' for a more accurate number of tests and therefore develop 'LD adjusted' Bonferroni corrected p-value thresholds that account for the interdepdendence of SNPs on well-utilized commercially available SNP "chips". These thresholds will serve as guides to researchers trying to decide which regions of the genome should be studied further.

journal_name

BMC Genomics

journal_title

BMC genomics

authors

Duggal P,Gillanders EM,Holmes TN,Bailey-Wilson JE

doi

10.1186/1471-2164-9-516

subject

Has Abstract

pub_date

2008-10-31 00:00:00

pages

516

issn

1471-2164

pii

1471-2164-9-516

journal_volume

9

pub_type

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