Title

Efficient mining of haplotype patterns for linkage disequilibrium mapping

Publication Type

Journal Article

Publication Date

12-2010

Abstract

Effective identification of disease-causing gene locations can have significant impact on patient management decisions that will ultimately increase survival rates and improve the overall quality of health care. Linkage disequilibrium mapping is the process of finding disease gene locations through comparisons of haplotype frequencies between disease chromosomes and normal chromosomes. This work presents a new method for linkage disequilibrium mapping. The main advantage of the proposed algorithm, called LinkageTracker, is its consistency in producing good predictive accuracy under different conditions, including extreme conditions where the occurrence of disease samples with the mutation of interest is very low and there is presence of error or noise. We compared our method with some leading methods in linkage disequilibrium mapping such as HapMiner, Blade, GeneRecon, and Haplotype Pattern Mining (HPM). Experimental results show that for a substantial class of problems, our method has good predictive accuracy while taking reasonably short processing time. Furthermore, LinkageTracker does not require any population ancestry information about the disease and the genealogy of the haplotypes. Therefore, it is useful for linkage disequilibrium mapping when the users do not have such information about their datasets. © 2010 The Authors.

Keywords

haplotypes, Linkage disequilibrium mapping, pattern mining

Discipline

Computer Sciences | Health Information Technology

Research Areas

Intelligent Systems and Decision Analytics

Publication

Journal of Bioinformatics and Computational Biology

Volume

8

Issue

1

First Page

127

Last Page

146

ISSN

0219-7200

Identifier

10.1142/S0219720010005142

Publisher

World Scientific Publishing

This document is currently not available here.

Share

COinS