Format

Send to

Choose Destination
See comment in PubMed Commons below
Genet Epidemiol. 2008 Apr;32(3):227-34. doi: 10.1002/gepi.20297.

Estimation of significance thresholds for genomewide association scans.

Author information

1
MRC Biostatistics Unit, Institute for Public Health, Cambridge, United Kingdom. frank.dudbridge@mrc-bsu.cam.ac.uk

Abstract

The question of what significance threshold is appropriate for genomewide association studies is somewhat unresolved. Previous theoretical suggestions have yet to be validated in practice, whereas permutation testing does not resolve a discrepancy between the genomewide multiplicity of the experiment and the subset of markers actually tested. We used genotypes from the Wellcome Trust Case-Control Consortium to estimate a genomewide significance threshold for the UK Caucasian population. We subsampled the genotypes at increasing densities, using permutation to estimate the nominal P-value for 5% family-wise error. By extrapolating to infinite density, we estimated the genomewide significance threshold to be about 7.2 x 10(-8). To reduce the computation time, we considered Patterson's eigenvalue estimator of the effective number of tests, but found it to be an order of magnitude too low for multiplicity correction. However, by fitting a Beta distribution to the minimum P-value from permutation replicates, we showed that the effective number is a useful heuristic and suggest that its estimation in this context is an open problem. We conclude that permutation is still needed to obtain genomewide significance thresholds, but with subsampling, extrapolation and estimation of an effective number of tests, the threshold can be standardized for all studies of the same population.

PMID:
18300295
PMCID:
PMC2573032
DOI:
10.1002/gepi.20297
[Indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Wiley Icon for PubMed Central
    Loading ...
    Support Center