A probability model for the meiosis I non-disjunction fraction in numerical XXXX .

@entity1 @entity1032 @entity2007 @entity1467 @entity2008 @entity393
@entity2008 ( @entity2007 ) are among the most common known causes of @entity1032 and the leading cause of @entity393 in @entity1 . They primarily arise by the process of meiotic non-disjunction. We still know very little about the contribution of genetic and environmental causes for non-disjunction in @entity1 . In order to increase our understanding of the epidemiology of @entity1 trisomies, it is necessary to establish the proportion of cases occurring in the first or second division of meiosis. Trisomic @entity1 will display, in study of microsatellite typed by the polymerase chain reaction (PCR), three fragment peaks of equal intensity, two fragments at an average 2:1 dosage or one individual fragment. In this work we describe a statistical approach for estimation of the fraction of meiosis I non-disjunctions (F) in the absence of the parental information. First we determine a probability model for the number of peaks in a polymorphic microsatellite locus, which is a function of F. Based on this model, we obtain a maximum likelihood estimator for F, using the observed proportion of one, two and three allele patterns in trisomic individuals. Relying on the properties of maximum likelihood theory, we also calculate the asymptotic variance and confidence intervals for F. Owing to the fact that the samples of trisomic @entity1 are limited in number, the use of asymptotic theory may be compromised. Thus, we employ the bootstrap technique to build confidence intervals for F and compare the results with those obtained from the normal theory. This estimator that dispenses the need to study parents opens the possibility of using archival material for comparative epidemiological studies of @entity1467 and other @entity2007 . In this paper we propose a probability model to estimate the fraction of meiosis I non-disjunction, F, by only using the proportion of allele patterns of trisomy individuals, while traditional methods require typing pericentromeric markers from those affected and their parents.
