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Improved IBD detection using incomplete haplotype information

BACKGROUND: The availability of high density genetic maps and genotyping platforms has transformed human genetic studies. The use of these platforms has enabled population-based genome-wide association studies. However, in inheritance-based studies, current methods do not take full advantage of the...

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Autores principales: Genovese, Giulio, Leibon, Gregory, Pollak, Martin R, Rockmore, Daniel N
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2914765/
https://www.ncbi.nlm.nih.gov/pubmed/20591167
http://dx.doi.org/10.1186/1471-2156-11-58
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author Genovese, Giulio
Leibon, Gregory
Pollak, Martin R
Rockmore, Daniel N
author_facet Genovese, Giulio
Leibon, Gregory
Pollak, Martin R
Rockmore, Daniel N
author_sort Genovese, Giulio
collection PubMed
description BACKGROUND: The availability of high density genetic maps and genotyping platforms has transformed human genetic studies. The use of these platforms has enabled population-based genome-wide association studies. However, in inheritance-based studies, current methods do not take full advantage of the information present in such genotyping analyses. RESULTS: In this paper we describe an improved method for identifying genetic regions shared identical-by-descent (IBD) from recent common ancestors. This method improves existing methods by taking advantage of phase information even if it is less than fully accurate or missing. We present an analysis of how using phase information increases the accuracy of IBD detection compared to using only genotype information. CONCLUSIONS: Our algorithm should have utility in a wide range of genetic studies that rely on identification of shared genetic material in large families or small populations.
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spelling pubmed-29147652010-08-04 Improved IBD detection using incomplete haplotype information Genovese, Giulio Leibon, Gregory Pollak, Martin R Rockmore, Daniel N BMC Genet Methodology Article BACKGROUND: The availability of high density genetic maps and genotyping platforms has transformed human genetic studies. The use of these platforms has enabled population-based genome-wide association studies. However, in inheritance-based studies, current methods do not take full advantage of the information present in such genotyping analyses. RESULTS: In this paper we describe an improved method for identifying genetic regions shared identical-by-descent (IBD) from recent common ancestors. This method improves existing methods by taking advantage of phase information even if it is less than fully accurate or missing. We present an analysis of how using phase information increases the accuracy of IBD detection compared to using only genotype information. CONCLUSIONS: Our algorithm should have utility in a wide range of genetic studies that rely on identification of shared genetic material in large families or small populations. BioMed Central 2010-06-30 /pmc/articles/PMC2914765/ /pubmed/20591167 http://dx.doi.org/10.1186/1471-2156-11-58 Text en Copyright ©2010 Genovese et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Genovese, Giulio
Leibon, Gregory
Pollak, Martin R
Rockmore, Daniel N
Improved IBD detection using incomplete haplotype information
title Improved IBD detection using incomplete haplotype information
title_full Improved IBD detection using incomplete haplotype information
title_fullStr Improved IBD detection using incomplete haplotype information
title_full_unstemmed Improved IBD detection using incomplete haplotype information
title_short Improved IBD detection using incomplete haplotype information
title_sort improved ibd detection using incomplete haplotype information
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2914765/
https://www.ncbi.nlm.nih.gov/pubmed/20591167
http://dx.doi.org/10.1186/1471-2156-11-58
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