Multipoint estimation of genetic maps for human trisomies with one parent or other partial data

Centromeric-mapping methods have been used to investigate the association b etween altered recombination and meiotic nondisjunction in humans. For tris omies, current methods are based on the genotypes from a trisomic offspring and both parents. Because it is sometimes difficult to obtain samples from both parents and because the ability to use sources of DNA previously not available (e.g., stored paraffin-embedded pathological samples) has increas ed, me have been interested in creating similar maps for trisomic populatio ns in which one of the parents of the trisomic individual is unavailable fo r genotyping. In this paper, we derive multipoint likelihoods for both miss ing-parent data and conventional two-parent data. We find that Likelihoods for two-parent data and for data generated without a sample from the correc tly disjoining parent can be maximized in exactly the same way but also tha t missing-parent data has a high frequency of partial data of the same sort produced by intercross matings. Previously published centromeric-mapping m ethods use incorrect likelihoods for intercross matings and thus can perfor m poorly on missing-parent data. We wrote a FORTRAN program to maximize our multipoint likelihoods and used it in simulation studies to demonstrate th e biases in the previous methods.