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Interval estimation of disease loci: development and applications of new linkage methods

Three variants of the confidence set inference (CSI) procedure were proposed and applied to both the simulated and the Collaborative Study on the Genetics of Alcoholism (COGA) data. For each of the two applications, we first performed a preliminary genome scan study based on the microsatellite marke...

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Detalles Bibliográficos
Autores principales: Papachristou, Charalampos, Lin, Shili
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866765/
https://www.ncbi.nlm.nih.gov/pubmed/16451630
http://dx.doi.org/10.1186/1471-2156-6-S1-S21
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author Papachristou, Charalampos
Lin, Shili
author_facet Papachristou, Charalampos
Lin, Shili
author_sort Papachristou, Charalampos
collection PubMed
description Three variants of the confidence set inference (CSI) procedure were proposed and applied to both the simulated and the Collaborative Study on the Genetics of Alcoholism (COGA) data. For each of the two applications, we first performed a preliminary genome scan study based on the microsatellite markers using the GENEHUNTER+ software to identify regions that potentially harbor disease loci. For each such region, we estimated the sibling identity-by-descent sharing probability distribution at the putative disease locus. Based on these estimated probabilities, the CSI procedures were employed to further localize the disease loci using the single-nucleotide polymorphism markers, leading to confidence intervals/regions for their locations. For our analysis with the simulated data, we had knowledge of the simulating models at the time we performed the analysis.
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spelling pubmed-18667652007-05-11 Interval estimation of disease loci: development and applications of new linkage methods Papachristou, Charalampos Lin, Shili BMC Genet Proceedings Three variants of the confidence set inference (CSI) procedure were proposed and applied to both the simulated and the Collaborative Study on the Genetics of Alcoholism (COGA) data. For each of the two applications, we first performed a preliminary genome scan study based on the microsatellite markers using the GENEHUNTER+ software to identify regions that potentially harbor disease loci. For each such region, we estimated the sibling identity-by-descent sharing probability distribution at the putative disease locus. Based on these estimated probabilities, the CSI procedures were employed to further localize the disease loci using the single-nucleotide polymorphism markers, leading to confidence intervals/regions for their locations. For our analysis with the simulated data, we had knowledge of the simulating models at the time we performed the analysis. BioMed Central 2005-12-30 /pmc/articles/PMC1866765/ /pubmed/16451630 http://dx.doi.org/10.1186/1471-2156-6-S1-S21 Text en Copyright © 2005 Papachristou and Lin; 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
Papachristou, Charalampos
Lin, Shili
Interval estimation of disease loci: development and applications of new linkage methods
title Interval estimation of disease loci: development and applications of new linkage methods
title_full Interval estimation of disease loci: development and applications of new linkage methods
title_fullStr Interval estimation of disease loci: development and applications of new linkage methods
title_full_unstemmed Interval estimation of disease loci: development and applications of new linkage methods
title_short Interval estimation of disease loci: development and applications of new linkage methods
title_sort interval estimation of disease loci: development and applications of new linkage methods
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866765/
https://www.ncbi.nlm.nih.gov/pubmed/16451630
http://dx.doi.org/10.1186/1471-2156-6-S1-S21
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