title: An exact maternal-fetal genotype incompatibility (MFG) test.
abstract: The maternal-fetal genotype incompatibility (MFG) test can be used for a variety of genetic applications concerning disease risk in offspring including testing for the presence of alleles that act directly through offspring genotypes (child allelic effects), alleles that act through maternal genotypes (maternal allelic effects), or maternal-fetal genotype incompatibilities. The log-linear version of the MFG model divides the genotype data into many cells, where each cell represents one of the possible mother, father, and child genotype combinations. Currently, tests of hypotheses about different allelic effects are accomplished by an asymptotic MFG test, but it is unknown if this is appropriate under conditions that produce small cell counts. In this report, we develop an exact MFG test that is based on the permutation distribution of cell counts. We determine by simulation the type I error and power of both the exact MFG test and the asymptotic MFG test for four different biologically relevant scenarios: a test of child allelic effects in the presence of maternal allelic effects, a test of maternal allelic effects in the presence of child allelic effects, and tests of maternal-fetal genotype incompatibility with and without child allelic effects. These simulations show that, in general, the exact test is slightly conservative whereas the asymptotic test is slightly anti-conservative. However, the asymptotic MFG test produces significantly inflated type I error rates under conditions with extreme null allele frequencies and sample sizes of 75, 100, and 150. Under these conditions, the exact test is clearly preferred over the asymptotic test. Under all other conditions that we tested, the user can safely choose either the exact test or the asymptotic test.
authors.affiliation: Department of Biostatistics, University of California, Los Angeles, California 90095-1766, USA.
authors.forename: Sonia L
authors.initials: SL
authors.lastname: Minassian
authors.forename: Christina G S
authors.initials: CG
authors.lastname: Palmer
authors.forename: Janet S
authors.initials: JS
authors.lastname: Sinsheimer
mesh_terms: D000328:Adult; D000465:Algorithms; D002648:Child; D003198:Computer Simulation; D005260:Female; D005787:Gene Frequency; D020022:Genetic Predisposition to Disease / Q000453:epidemiology / Q000235:genetics*; D005820:Genetic Testing; D005838:Genotype; D006801:Humans; D008297:Male; D012307:Risk Factors; D018401:Sample Size