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A rapid conditional enumeration haplotyping method in pedigrees
Haplotyping in pedigrees provides valuable information for genetic studies (e.g., linkage analysis and association study). In order to identify a set of haplotype configurations with the highest likelihoods for a large pedigree with a large number of linked loci, in our previous work, we proposed a...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2008
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2674916/ https://www.ncbi.nlm.nih.gov/pubmed/18096113 http://dx.doi.org/10.1186/1297-9686-40-1-25 |
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author | Gao, Guimin Hoeschele, Ina |
author_facet | Gao, Guimin Hoeschele, Ina |
author_sort | Gao, Guimin |
collection | PubMed |
description | Haplotyping in pedigrees provides valuable information for genetic studies (e.g., linkage analysis and association study). In order to identify a set of haplotype configurations with the highest likelihoods for a large pedigree with a large number of linked loci, in our previous work, we proposed a conditional enumeration haplotyping method which sets a threshold for the conditional probabilities of the possible ordered genotypes at every unordered individual-marker to delete some ordered genotypes with low conditional probabilities and then eliminate some haplotype configurations with low likelihoods. In this article we present a rapid haplotyping algorithm based on a modification of our previous method by setting an additional threshold for the ratio of the conditional probability of a haplotype configuration to the largest conditional probability of all haplotype configurations in order to eliminate those configurations with relatively low conditional probabilities. The new algorithm is much more efficient than our previous method and the widely used software SimWalk2. |
format | Text |
id | pubmed-2674916 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-26749162009-04-30 A rapid conditional enumeration haplotyping method in pedigrees Gao, Guimin Hoeschele, Ina Genet Sel Evol Research Haplotyping in pedigrees provides valuable information for genetic studies (e.g., linkage analysis and association study). In order to identify a set of haplotype configurations with the highest likelihoods for a large pedigree with a large number of linked loci, in our previous work, we proposed a conditional enumeration haplotyping method which sets a threshold for the conditional probabilities of the possible ordered genotypes at every unordered individual-marker to delete some ordered genotypes with low conditional probabilities and then eliminate some haplotype configurations with low likelihoods. In this article we present a rapid haplotyping algorithm based on a modification of our previous method by setting an additional threshold for the ratio of the conditional probability of a haplotype configuration to the largest conditional probability of all haplotype configurations in order to eliminate those configurations with relatively low conditional probabilities. The new algorithm is much more efficient than our previous method and the widely used software SimWalk2. BioMed Central 2008-01-15 /pmc/articles/PMC2674916/ /pubmed/18096113 http://dx.doi.org/10.1186/1297-9686-40-1-25 Text en Copyright © 2008 INRA, EDP Sciences |
spellingShingle | Research Gao, Guimin Hoeschele, Ina A rapid conditional enumeration haplotyping method in pedigrees |
title | A rapid conditional enumeration haplotyping method in pedigrees |
title_full | A rapid conditional enumeration haplotyping method in pedigrees |
title_fullStr | A rapid conditional enumeration haplotyping method in pedigrees |
title_full_unstemmed | A rapid conditional enumeration haplotyping method in pedigrees |
title_short | A rapid conditional enumeration haplotyping method in pedigrees |
title_sort | rapid conditional enumeration haplotyping method in pedigrees |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2674916/ https://www.ncbi.nlm.nih.gov/pubmed/18096113 http://dx.doi.org/10.1186/1297-9686-40-1-25 |
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