Fast Computation of Human Genetic Linkage

Hongling Wang; A.M Segre; Yungui Huang; J.R O'Connell; V.J Vieland

doi:10.1109/BIBE.2007.4375660

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Conference proceeding

Fast Computation of Human Genetic Linkage

Hongling Wang, A.M Segre, Yungui Huang, J.R O'Connell and V.J Vieland

2007 IEEE 7th International Symposium on BioInformatics and BioEngineering, Vol.7, pp.857-863

10/2007

DOI: 10.1109/BIBE.2007.4375660

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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.

Bioinformatics

Biological cells

Chromosome mapping

Couplings

Diseases

Genetics

Genomics

Humans

Pediatrics

Statistical analysis

Details

Title: Subtitle: Fast Computation of Human Genetic Linkage
Creators: Hongling Wang - Columbus Children's Res. Inst., Columbus
A.M Segre - University of Iowa
Yungui Huang - Community College of Rhode Island
J.R O'Connell - University of Maryland, Baltimore
V.J Vieland - The Ohio State University
Resource Type: Conference proceeding
Publication Details: 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering, Vol.7, pp.857-863
DOI: 10.1109/BIBE.2007.4375660
Publisher: IEEE
Language: English
Date published: 10/2007
Academic Unit: Nursing; Fraternal Order of Eagles Diabetes Research Center; Computer Science
Record Identifier: 9984259476302771

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