Data Mining Applied to Linkage Disequilibrium Mapping

Data mining applied to linkage disequilibrium mapping.

We introduce a new method for linkage disequilibrium mapping: haplotype pattern mining (HPM). The method, inspired by data mining methods, is based on discovery of recurrent patterns. We define a class of useful haplotype patterns in genetic case-control data and use the algorithm for finding disease-associated haplotypes. The haplotypes are ordered by their strength of association with the phe...

Haplotype-based linkage disequilibrium mapping via direct data mining

MOTIVATION With the availability of large-scale, high-density single-nucleotide polymorphism markers and information on haplotype structures and frequencies, a great challenge is how to take advantage of haplotype information in the association mapping of complex diseases in case-control studies. RESULTS We present a novel approach for association mapping based on directly mining haplotypes (...

Bolck Linkage Disequilibrium Mapping

1. Abstract 2. Introduction 3. Models and methods 3.1. Haplotype block characterization 3.2. Measure of haplotype block LD 3.3. Test statistic and power calculation 3.4. Population genetic model of haplotype block 4. Results 4.1. Haplotype block LD measure 4.2. Power of the haplotype block LD mapping 4.3. Mapping 5. Discussion 6. Appendix 6.1. Appendix A 6.2. Appendix B 6.3. Appendix C 7. Refer...

Efficient mining of haplotype patterns for linkage disequilibrium mapping.

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 wor...

linkage disequilibrium and association mapping