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Genotype imputation via matrix completion

Most current genotype imputation methods are model-based and computationally intensive, taking days to impute one chromosome pair on 1000 people. We describe an efficient genotype imputation method based on matrix completion. Our matrix completion method is implemented in MATLAB and tested on real d...

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Detalles Bibliográficos
Autores principales: Chi, Eric C., Zhou, Hua, Chen, Gary K., Del Vecchyo, Diego Ortega, Lange, Kenneth
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3589539/
https://www.ncbi.nlm.nih.gov/pubmed/23233546
http://dx.doi.org/10.1101/gr.145821.112
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author Chi, Eric C.
Zhou, Hua
Chen, Gary K.
Del Vecchyo, Diego Ortega
Lange, Kenneth
author_facet Chi, Eric C.
Zhou, Hua
Chen, Gary K.
Del Vecchyo, Diego Ortega
Lange, Kenneth
author_sort Chi, Eric C.
collection PubMed
description Most current genotype imputation methods are model-based and computationally intensive, taking days to impute one chromosome pair on 1000 people. We describe an efficient genotype imputation method based on matrix completion. Our matrix completion method is implemented in MATLAB and tested on real data from HapMap 3, simulated pedigree data, and simulated low-coverage sequencing data derived from the 1000 Genomes Project. Compared with leading imputation programs, the matrix completion algorithm embodied in our program MENDEL-IMPUTE achieves comparable imputation accuracy while reducing run times significantly. Implementation in a lower-level language such as Fortran or C is apt to further improve computational efficiency.
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spelling pubmed-35895392013-09-01 Genotype imputation via matrix completion Chi, Eric C. Zhou, Hua Chen, Gary K. Del Vecchyo, Diego Ortega Lange, Kenneth Genome Res Method Most current genotype imputation methods are model-based and computationally intensive, taking days to impute one chromosome pair on 1000 people. We describe an efficient genotype imputation method based on matrix completion. Our matrix completion method is implemented in MATLAB and tested on real data from HapMap 3, simulated pedigree data, and simulated low-coverage sequencing data derived from the 1000 Genomes Project. Compared with leading imputation programs, the matrix completion algorithm embodied in our program MENDEL-IMPUTE achieves comparable imputation accuracy while reducing run times significantly. Implementation in a lower-level language such as Fortran or C is apt to further improve computational efficiency. Cold Spring Harbor Laboratory Press 2013-03 /pmc/articles/PMC3589539/ /pubmed/23233546 http://dx.doi.org/10.1101/gr.145821.112 Text en © 2013, Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by-nc/3.0/ This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 3.0 Unported License), as described at http://creativecommons.org/licenses/by-nc/3.0/.
spellingShingle Method
Chi, Eric C.
Zhou, Hua
Chen, Gary K.
Del Vecchyo, Diego Ortega
Lange, Kenneth
Genotype imputation via matrix completion
title Genotype imputation via matrix completion
title_full Genotype imputation via matrix completion
title_fullStr Genotype imputation via matrix completion
title_full_unstemmed Genotype imputation via matrix completion
title_short Genotype imputation via matrix completion
title_sort genotype imputation via matrix completion
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3589539/
https://www.ncbi.nlm.nih.gov/pubmed/23233546
http://dx.doi.org/10.1101/gr.145821.112
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