A multilocus model for constructing a linkage disequilibrium map in human populations

Qin Li, Rongling Wu

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

The extent and pattern of linkage disequilibrium (LD) determine the feasibility of association studies to map genes that underlie complex traits. Here we present a statistical algorithm for constructing a joint linkage-linkage disequilibrium map by simultaneously estimating the recombination fraction and linkage disequilibrium between different molecular markers in a natural human population. This algorithm was devised with a set of random unrelated families, each including a father, a mother and a varying number of offspring, sampled from a population at Hardy-Weinberg equilibrium. A two-level hierarchical mixture model framework was built, in which the likelihood of genotype data for the parents was formulated in terms of linkage disequilibrium at an upper level, whereas the likelihood of genetic transmission from the parents to offspring formulated in terms of the recombination fraction at a lower level. The EM algorithm was implemented to obtain a closed system of maximum likelihood estimates of marker co-segregation and co-transmission. The model allows a number of testable hypotheses about population genetic parameters, opening a broad gateway to understand the genetic structure and dynamics of an outcrossing population under natural selection. The new strategy will provide a platform for studying the genetic control of inherited diseases in which genetic material is accurately copied before being passed onto the offspring from a parent.

Original languageEnglish (US)
Article number18
JournalStatistical Applications in Genetics and Molecular Biology
Volume8
Issue number1
DOIs
StatePublished - Apr 20 2009

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Linkage Disequilibrium
Recombination
Genetic Recombination
Population
Likelihood
Parents
Likelihood Functions
Maximum likelihood
Natural Selection
Population Genetics
Genetic Structures
Genetic Selection
Gateway
Population Dynamics
Feasibility Studies
Hierarchical Model
Segregation
EM Algorithm
Genes
Maximum Likelihood Estimate

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Molecular Biology
  • Genetics
  • Computational Mathematics

Cite this

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