Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network

  Advanced Search  

Genetic Epidemiology 30: 384396 (2006) Using Sex-Averaged Genetic Maps in Multipoint Linkage Analysis

Summary: Genetic Epidemiology 30: 384396 (2006)
Using Sex-Averaged Genetic Maps in Multipoint Linkage Analysis
When Identity-by-Descent Status is Incompletely Known
Tasha E. Fingerlin,1 Gonc-alo R. Abecasis2
and Michael Boehnke2
Department of Preventive Medicine and Biometrics, School of Medicine, University of Colorado at Denver and Health Sciences Center, Denver, Colorado
Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, Michigan
The ratio of male and female genetic map distances varies dramatically across the human genome. Despite these sex
differences in genetic map distances, most multipoint linkage analyses use sex-averaged genetic maps. We investigated the
impact of using a sex-averaged genetic map instead of sex-specific maps for multipoint linkage analysis of affected sibling
pairs when identity-by-descent states are incompletely known due to missing parental genotypes and incomplete marker
heterozygosity. If either all or no parental genotypes were available, for intermarker distances of 10, 5, and 1 cM, we found
no important differences in the expected maximum lod score (EMLOD) or location estimates of the disease locus between
analyses that used the sex-averaged map and those that used the true sex-specific maps for female:male genetic map
distance ratios 1:10 and 10:1. However, when genotypes for only one parent were available and the recombination rate was
higher in females, the EMLOD using the sex-averaged map was inflated compared to the sex-specific map analysis if only
mothers were genotyped and deflated if only fathers were genotyped. The inflation of the lod score when only mothers
were genotyped led to markedly increased false-positive rates in some cases. The opposite was true when the recombination


Source: Abecasis, Goncalo - Department of Biostatistics, University of Michigan


Collections: Biology and Medicine; Mathematics