SEQUENTIAL IMPUTATION FOR MULTILOCUS LINKAGE ANALYSIS

被引：32

作者：

IRWIN, M

COX, N

KONG, A

机构：

[1] UNIV CHICAGO,DEPT MED,CHICAGO,IL 60637

[2] UNIV CHICAGO,DEPT STAT,CHICAGO,IL 60637

来源：

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA | 1994年 / 91卷 / 24期

关键词：

D O I：

10.1073/pnas.91.24.11684

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页码：11684 / 11688

页数：5

共 20 条

[1] GENE FOR NON-INSULIN-DEPENDENT DIABETES-MELLITUS (MATURITY-ONSET DIABETES OF THE YOUNG SUBTYPE) IS LINKED TO DNA POLYMORPHISM ON HUMAN CHROMOSOME-20Q [J].