Traditional linkage analysis in admixed families
Abstract
Currently there is no general method to study the impact of population admixture within families on the assumptions of random mating and consequently, Hardy-Weinberg equilibrium (HWE) and linkage equilibrium (LE) and on the inference obtained from traditional linkage analysis. First, through simulation, the effect of admixture of two populations on the log of the odds (LOD) score was assessed, using Prostate Cancer as the typical disease model. Comparisons between simulated mixed and homogeneous families were performed. LOD scores under both models of admixture (within families and within a data set of homogeneous families) were closest to the homogeneous family scores of the population having the highest mixing proportion. Random sampling of families or ascertainment of families with disease affection status did not affect this observation, nor did the mode of inheritance (dominant/recessive) or sample size. Second, after establishing the effect of admixture on the LOD score and inference for linkage, the presence of induced disequilibria by population admixture within families was studied and an adjustment procedure was developed. The adjustment did not force all disequilibria to disappear but because the families were adjusted for the population admixture, those replicates where the disequilibria exist are no longer affected by the disequilibria in terms of maximization for linkage. Furthermore, the adjustment was able to exclude uninformative families or families that had such a high departure from HWE and/or LE that their LOD scores were not reliable. Together these observations imply that the presence of families of mixed population ancestry impacts linkage analysis in terms of the LOD score and the estimate of the recombination fraction.
Subject Area
Biostatistics
Recommended Citation
Barnholtz, Jill Suzanne, "Traditional linkage analysis in admixed families" (2000). Texas Medical Center Dissertations (via ProQuest). AAI9981806.
https://digitalcommons.library.tmc.edu/dissertations/AAI9981806