Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
Am. J. Hum. Genet. 77:754767, 2005 Handling Marker-Marker Linkage Disequilibrium: Pedigree Analysis
 

Summary: Am. J. Hum. Genet. 77:754­767, 2005
754
Handling Marker-Marker Linkage Disequilibrium: Pedigree Analysis
with Clustered Markers
Gonc¸alo R. Abecasis and Janis E. Wigginton
Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor
Single-nucleotide polymorphisms (SNPs) are rapidly replacing microsatellites as the markers of choice for genetic
linkage studies and many other studies of human pedigrees. Here, we describe an efficient approach for modeling
linkage disequilibrium (LD) between markers during multipoint analysis of human pedigrees. Using a gene-counting
algorithm suitable for pedigree data, our approach enables rapid estimation of allele and haplotype frequencies
within clusters of tightly linked markers. In addition, with the use of a hidden Markov model, our approach allows
for multipoint pedigree analysis with large numbers of SNP markers organized into clusters of markers in LD.
Simulation results show that our approach resolves previously described biases in multipoint linkage analysis with
SNPs that are in LD. An updated version of the freely available Merlin software package uses the approach described
here to perform many common pedigree analyses, including haplotyping and haplotype frequency estimation,
parametric and nonparametric multipoint linkage analysis of discrete traits, variance-components and regression-
based analysis of quantitative traits, calculation of identity-by-descent or kinship coefficients, and case selection
for follow-up association studies. To illustrate the possibilities, we examine a data set that provides evidence of
linkage of psoriasis to chromosome 17.
Introduction

  

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

 

Collections: Biology and Medicine; Mathematics