DocumentCode :
1990973
Title :
Fast Computation of Human Genetic Linkage
Author :
Wang, Hongling ; Segre, Alberto Maria ; Huang, Yungui ; Connell, Jeffrey R O ; Vieland, Veronica J.
Author_Institution :
Columbus Children´´s Res. Inst., Columbus
fYear :
2007
fDate :
14-17 Oct. 2007
Firstpage :
857
Lastpage :
863
Abstract :
Genetic linkage analysis is a recombinant technology used for mapping disease genes on the genome, based on genotypic and phenotypic data collected from families that have affected members. The LOD score is a commonly used statistic in genetic linkage analysis. LOD scores are computed assuming specific values for genetic parameters. However, for complex disorders the specified parameter values are often unknown. One way to address this issue is to maximize the LOD score over all genetic parameters to get a maximum LOD score, or MOD score. Another way is to integrate the LOD score across the genetic parameters to form a posterior probability of linkage, or PPL. Both methods require calculation of large numbers of LOD scores under different sets of parameter values. These calculations may be very time-consuming and can form a significant bottleneck in disease gene mapping. The motivation for this work is to speed up the computation of large numbers of LOD scores in linkage analysis. Instead of the usual LOD calculation where the likelihood of a pedigree under each set of parameter values is computed based on traversing the pedigree, the likelihood of the pedigree is computed here as an algebraic expression that can be optimized and reused. This optimized likelihood expression can be evaluated an arbitrary number of times for LOD scores under different values of the genetic parameters, resulting in much faster speeds. Our initial results show that this approach can speed up the traditional genetic linkage computation by 10~1200 times.
Keywords :
biocomputing; cellular biophysics; diseases; genetics; molecular biophysics; LOD score; MOD score; algebraic expression; complex disorders; disease gene mapping; fast computation; genetic parameters; genome; genotypic data; human genetic linkage; phenotypic data; posterior probability-of-linkage; recombinant technology; Bioinformatics; Biological cells; Chromosome mapping; Couplings; Diseases; Genetics; Genomics; Humans; Pediatrics; Statistical analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Bioengineering, 2007. BIBE 2007. Proceedings of the 7th IEEE International Conference on
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-1509-0
Type :
conf
DOI :
10.1109/BIBE.2007.4375660
Filename :
4375660
Link To Document :
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