Sequential imputation for multilocus linkage analysis

Proc Natl Acad Sci U S A. 1994 Nov 22;91(24):11684-8. doi: 10.1073/pnas.91.24.11684.


A Monte Carlo method called sequential imputation is proposed for multilocus likelihood computations. This method is most useful in mapping situations where the data consist of large pedigrees with substantial missing information and it is desirable to perform linkage analysis utilizing data from many polymorphic markers simultaneously. A pedigree example with 155 individuals, 9 loci, and 155,520 haplotypes is used for illustration.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Diabetes Mellitus, Type 2 / genetics
  • Female
  • Genetic Linkage*
  • Humans
  • Likelihood Functions*
  • Male
  • Monte Carlo Method
  • Pedigree