Open AccessA maximum likelihood algorithm for genome mapping of cytogenetic loci from meiotic configuration data.
Author(s) -
M. H. Reyes-Valdés,
David M. Stelly
Publication year - 1995
Publication title -
proceedings of the national academy of sciences of the united states of america
Language(s) - English
Resource type - Journals
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.92.21.9824
Subject(s) - chiasma , meiosis , algorithm , expectation–maximization algorithm , breakpoint , biology , genetics , centromere , data set , pooling , maximum likelihood , mathematics , statistics , chromosome , computational biology , computer science , artificial intelligence , gene
Frequencies of meiotic configurations in cytogenetic stocks are dependent on chiasma frequencies in segments defined by centromeres, breakpoints, and telomeres. The expectation maximization algorithm is proposed as a general method to perform maximum likelihood estimations of the chiasma frequencies in the intervals between such locations. The estimates can be translated via mapping functions into genetic maps of cytogenetic landmarks. One set of observational data was analyzed to exemplify application of these methods, results of which were largely concordant with other comparable data. The method was also tested by Monte Carlo simulation of frequencies of meiotic configurations from a monotelodisomic translocation heterozygote, assuming six different sample sizes. The estimate averages were always close to the values given initially to the parameters. The maximum likelihood estimation procedures can be extended readily to other kinds of cytogenetic stocks and allow the pooling of diverse cytogenetic data to collectively estimate lengths of segments, arms, and chromosomes.