Haplotype inference in general pedigrees using the cluster variation method. Export

@article{citeulike:1868454, abstract = {We present CVMHAPLO, a probabilistic method for haplotyping in general pedigrees with many markers. CVMHAPLO reconstructs the haplotypes by assigning in every iteration a fixed number of the ordered genotypes with the highest marginal probability, conditioned on the marker data and ordered genotypes assigned in previous iterations. CVMHAPLO makes use of the cluster variation method (CVM) to efficiently estimate the marginal probabilities. We focused on single-nucleotide polymorphism (SNP) markers in the evaluation of our approach. In simulated data sets where exact computation was feasible, we found that the accuracy of CVMHAPLO was high and similar to that of maximum-likelihood methods. In simulated data sets where exact computation of the maximum-likelihood haplotype configuration was not feasible, the accuracy of CVMHAPLO was similar to that of state of the art Markov chain Monte Carlo (MCMC) maximum-likelihood approximations when all ordered genotypes were assigned and higher when only a subset of the ordered genotypes was assigned. CVMHAPLO was faster than the MCMC approach and provided more detailed information about the uncertainty in the inferred haplotypes. We conclude that CVMHAPLO is a practical tool for the inference of haplotypes in large complex pedigrees.}, author = {Albers, C. A. and Heskes, T. and Kappen, H. J.}, citeulike-article-id = {1868454}, citeulike-linkout-0 = {http://dx.doi.org/10.1534/genetics.107.074047}, citeulike-linkout-1 = {http://www.genetics.org/cgi/content/abstract/177/2/1101}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/17660564}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=17660564}, day = {1}, doi = {10.1534/genetics.107.074047}, issn = {0016-6731}, journal = {Genetics}, keywords = {haplotype}, month = {October}, number = {2}, pages = {1101--1116}, posted-at = {2007-11-05 13:46:46}, priority = {3}, title = {Haplotype inference in general pedigrees using the cluster variation method.}, url = {http://dx.doi.org/10.1534/genetics.107.074047}, volume = {177}, year = {2007} }

TY - JOUR ID - citeulike:1868454 L3 - citeulike-article-id:1868454 N2 - We present CVMHAPLO, a probabilistic method for haplotyping in general pedigrees with many markers. CVMHAPLO reconstructs the haplotypes by assigning in every iteration a fixed number of the ordered genotypes with the highest marginal probability, conditioned on the marker data and ordered genotypes assigned in previous iterations. CVMHAPLO makes use of the cluster variation method (CVM) to efficiently estimate the marginal probabilities. We focused on single-nucleotide polymorphism (SNP) markers in the evaluation of our approach. In simulated data sets where exact computation was feasible, we found that the accuracy of CVMHAPLO was high and similar to that of maximum-likelihood methods. In simulated data sets where exact computation of the maximum-likelihood haplotype configuration was not feasible, the accuracy of CVMHAPLO was similar to that of state of the art Markov chain Monte Carlo (MCMC) maximum-likelihood approximations when all ordered genotypes were assigned and higher when only a subset of the ordered genotypes was assigned. CVMHAPLO was faster than the MCMC approach and provided more detailed information about the uncertainty in the inferred haplotypes. We conclude that CVMHAPLO is a practical tool for the inference of haplotypes in large complex pedigrees. IS - 2 JF - Genetics SN - 0016-6731 EP - 1116 TI - Haplotype inference in general pedigrees using the cluster variation method. VL - 177 SP - 1101 KW - haplotype AU - Albers, CA AU - Heskes, T AU - Kappen, HJ PY - 2007/10/01/ UR - http://dx.doi.org/10.1534/genetics.107.074047 ER -