A Unified Approach to Adjusting Association Tests for Population Admixture with Arbitrary Pedigree Structure and Arbitrary Missing Marker Information

TLDR

The paper proposes a general approach for family‑based association testing between marker alleles and traits. The method computes p‑values by comparing test statistics to their conditional distributions given the minimal sufficient statistic under the null, enabling any test statistic, phenotype, multi‑allelic marker, covariate, pedigree structure, and missing marker pattern. The approach yields correct type‑I error rates regardless of population admixture, genetic model, or sampling strategy, and an algorithm for computing the conditional distributions is provided with results for nuclear families.

Abstract

A general approach to family-based examinations of association between marker alleles and traits is proposed. The approach is based on computing p values by comparing test statistics for association to their conditional distributions given the minimal sufficient statistic under the null hypothesis for the genetic model, sampling plan and population admixture. The approach can be applied with any test statistic, so any kind of phenotype and multi-allelic markers may be examined, and covariates may be included in analyses. By virtue of the conditioning, the approach results in correct type I error probabilities regardless of population admixture, the true genetic model and the sampling strategy. An algorithm for computing the conditional distributions is described, and the results of the algorithm for configurations of nuclear families are presented. The algorithm is applicable with all pedigree structures and all patterns of missing marker allele information.