Multiple testing corrections for imputed SNPs

Genet Epidemiol. 2011 Apr;35(3):154-8. doi: 10.1002/gepi.20563. Epub 2011 Jan 19.


Multiple testing corrections are an active research topic in genetic association studies, especially for genome-wide association studies (GWAS), where tests of association with traits are conducted at millions of imputed SNPs with estimated allelic dosages now. Failure to address multiple comparisons appropriately can introduce excess false-positive results and make subsequent studies following up those results inefficient. Permutation tests are considered the gold standard in multiple testing adjustment; however, this procedure is computationally demanding, especially for GWAS. Notably, the permutation thresholds for the huge number of estimated allelic dosages in real data sets have not been reported. Although many researchers have recently developed algorithms to rapidly approximate the permutation thresholds with accuracy similar to the permutation test, these methods have not been verified with estimated allelic dosages. In this study, we compare recently published multiple testing correction methods using 2.5M estimated allelic dosages. We also derive permutation significance levels based on 10,000 GWAS results under the null hypothesis of no association. Our results show that the simpleM method works well with estimated allelic dosages and gives the closest approximation to the permutation threshold while requiring the least computation time.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Alleles
  • Databases, Nucleic Acid / statistics & numerical data
  • Genome-Wide Association Study / statistics & numerical data*
  • Humans
  • Models, Genetic
  • Models, Statistical
  • Molecular Epidemiology / statistics & numerical data
  • Polymorphism, Single Nucleotide*