Summarizing and Quantifying Multilocus Linkage Disequilibrium Patterns with Multi-Order Markov Chain Models

被引：1

作者：

Feng, Sheng ^{[1
]}

Wang, Shengchu ^{[1
]}

机构：

[1] Duke Univ, Dept Biostat & Bioinformat, Durham, NC 27705 USA

来源：

JOURNAL OF BIOPHARMACEUTICAL STATISTICS | 2010年 / 20卷 / 02期

基金：

美国国家卫生研究院;

关键词：

Gene-disease association mapping; Linkage disequilibrium (LD); Multi-order Markov chain model; ENTROPY;

D O I：

10.1080/10543400903572837

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

Studies on linkage disequilibrium (LD) are important in mapping disease genes. A novel statistical method, the multi-order Markov chain model has been recently developed to quantify the complexity level of multilocus LD patterns among single nucleotide polymorphism markers (Kim et al., 2008). In this study, mathematical relationships between two types of LD measures are derived to understand the Markov chain model parameters in terms of conventional LD measures. Statistical sample properties of the Markov chain order estimates are investigated by simulations. Two published data sets are reanalyzed to illustrate the proposed approach.

引用

页码：441 / 453

页数：13

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