DocumentCode :
3232673
Title :
An EM method based on entropy LD block partition for haplotype inference
Author :
Xu, Yun ; Wang, Ying ; Yao, Xiaohui ; Zhao, Yuzhong
Author_Institution :
Dept. of Comput. Sci., Univ. of Sci. & Technol. of China, Hefei, China
fYear :
2010
fDate :
23-26 Sept. 2010
Firstpage :
163
Lastpage :
167
Abstract :
Genetic diseases have attracted much attention to the genetic research which depends on the data named haplotypes. Because of most haplotypes are generated from genotypes, haplotype inference (HI) problem becomes very popular. To solve this problem, we propose a new method based on EM and partition-ligation (PL) strategy. Compared to the previous methods, our algorithm uses the PL strategy based on multilocus linkage disequilibrium (LD), which has an advantage over the uniform block partition and pairwise LD. Considering the scale of data and the missing alleles, we also change the ligation strategy to control the complexity of time and space. The experimental results on the real data and the simulated data show that the algorithm in this paper has better performance than previous ones.
Keywords :
diseases; expectation-maximisation algorithm; genetics; inference mechanisms; medical computing; EM method; entropy LD block partition; genetic diseases; genetic research; genotypes; haplotype inference problem; multilocus linkage disequilibrium; partition-ligation strategy; Accuracy; Bioinformatics; Biological cells; Genomics; expectation maximization; haplotype inference; linkage disequilibrium;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-6437-1
Type :
conf
DOI :
10.1109/BICTA.2010.5645337
Filename :
5645337
Link To Document :
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