Linkage mapping of total cholesterol level in a young cohort via nonparametric regression

BACKGROUND: Compared to model-based approaches, nonparametric methods for quantitative trait loci mapping are more robust to deviations in distributional assumptions. In this study, we modify a nonparametric regression method and the "contrast function"- based regression method to analyze...

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Detalles Bibliográficos
Autores principales: Ghosh, Saurabh, Bertelsen, Sarah, Reich, Theodore
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2003
Materias:
Proceedings
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866533/
https://www.ncbi.nlm.nih.gov/pubmed/14975160
http://dx.doi.org/10.1186/1471-2156-4-S1-S92
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author Ghosh, Saurabh
Bertelsen, Sarah
Reich, Theodore
author_facet Ghosh, Saurabh
Bertelsen, Sarah
Reich, Theodore
author_sort Ghosh, Saurabh
collection PubMed
description BACKGROUND: Compared to model-based approaches, nonparametric methods for quantitative trait loci mapping are more robust to deviations in distributional assumptions. In this study, we modify a nonparametric regression method and the "contrast function"- based regression method to analyze total cholesterol level in the younger cohort (the offspring generation) of the Genetic Analysis Workshop 13 simulated data set. RESULTS: We obtained significant evidence of linkage near four of the six non-sex-specific genes in at least 30% of the replicates. CONCLUSIONS: The proposed nonparametric method seems to be a powerful robust alternative to distribution-based methods.
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spelling pubmed-18665332007-05-11 Linkage mapping of total cholesterol level in a young cohort via nonparametric regression Ghosh, Saurabh Bertelsen, Sarah Reich, Theodore BMC Genet Proceedings BACKGROUND: Compared to model-based approaches, nonparametric methods for quantitative trait loci mapping are more robust to deviations in distributional assumptions. In this study, we modify a nonparametric regression method and the "contrast function"- based regression method to analyze total cholesterol level in the younger cohort (the offspring generation) of the Genetic Analysis Workshop 13 simulated data set. RESULTS: We obtained significant evidence of linkage near four of the six non-sex-specific genes in at least 30% of the replicates. CONCLUSIONS: The proposed nonparametric method seems to be a powerful robust alternative to distribution-based methods. BioMed Central 2003-12-31 /pmc/articles/PMC1866533/ /pubmed/14975160 http://dx.doi.org/10.1186/1471-2156-4-S1-S92 Text en Copyright © 2003 Ghosh 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 Proceedings
Ghosh, Saurabh
Bertelsen, Sarah
Reich, Theodore
Linkage mapping of total cholesterol level in a young cohort via nonparametric regression
title Linkage mapping of total cholesterol level in a young cohort via nonparametric regression
title_full Linkage mapping of total cholesterol level in a young cohort via nonparametric regression
title_fullStr Linkage mapping of total cholesterol level in a young cohort via nonparametric regression
title_full_unstemmed Linkage mapping of total cholesterol level in a young cohort via nonparametric regression
title_short Linkage mapping of total cholesterol level in a young cohort via nonparametric regression
title_sort linkage mapping of total cholesterol level in a young cohort via nonparametric regression
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866533/
https://www.ncbi.nlm.nih.gov/pubmed/14975160
http://dx.doi.org/10.1186/1471-2156-4-S1-S92
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AT reichtheodore linkagemappingoftotalcholesterollevelinayoungcohortvianonparametricregression

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