A Unified Approach to Adjusting Association Tests for Population Admixture with Arbitrary Pedigree Structure and Arbitrary Missing Marker Information
Daniel Rabinowitza b, Nan M. Lairdc
- aDepartment of Statistics, Columbia University, New York, N.Y., USA. dan@stat.columbia.edu
- bDepartment of Statistics, Columbia University, New York, N.Y., and
- cDepartment of Biostatistics, Harvard School of Public Health, Boston, Mass., USA
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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.
TL;DRA general approach to family-based examinations of association between marker alleles and traits is proposed, based on computing p values by comparing test statistics for association to their conditional distributions given the minimal sufficient statistic under the null hypothesis. (Semantic Scholar)