Exact Inference for Hardy-Weinberg Proportions with Missing Genotypes: Single and Multiple Imputation.

Abstract

This paper addresses the issue of exact-test based statistical inference for Hardy-Weinberg equilibrium in the presence of missing genotype data. Missing genotypes are often discarded when markers are tested for Hardy-Weinberg equilibrium and this can lead to bias in the statistical inference about equilibrium. Single and multiple imputation can improve inference on equilibrium. We develop tests for equilibrium in the presence of missingness using both inbreeding coefficients (or, equivalently, chi-square statistics) and exact p-values. The analysis of a set of markers with a high missing rate from the GENEVA project on prematurity shows that exact inference on equilibrium can be altered considerably when missingness is taken into account. For markers with a high missing rate (>5%) we found that both single and multiple imputation tend to diminish evidence for Hardy-Weinberg disequilibrium. Depending on the imputation method used, six through thirteen percent of the test results changed qualitatively at the five percent level.