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Examining the effect of linkage disequilibrium on multipoint linkage analysis
Most linkage programs assume linkage equilibrium among multiple linked markers. This assumption may lead to bias for tightly linked markers where strong linkage disequilibrium (LD) exists. We used simulated data from Genetic Analysis Workshop 14 to examine the possible effect of LD on multipoint lin...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2005
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866697/ https://www.ncbi.nlm.nih.gov/pubmed/16451698 http://dx.doi.org/10.1186/1471-2156-6-S1-S83 |
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author | Huang, Qiqing Shete, Sanjay Swartz, Michael Amos, Christopher I |
author_facet | Huang, Qiqing Shete, Sanjay Swartz, Michael Amos, Christopher I |
author_sort | Huang, Qiqing |
collection | PubMed |
description | Most linkage programs assume linkage equilibrium among multiple linked markers. This assumption may lead to bias for tightly linked markers where strong linkage disequilibrium (LD) exists. We used simulated data from Genetic Analysis Workshop 14 to examine the possible effect of LD on multipoint linkage analysis. Single-nucleotide polymorphism packets from a non-disease-related region that was generated with LD were used for both model-free and parametric linkage analyses. Results showed that high LD among markers can induce false-positive evidence of linkage for affected sib-pair analysis when parental data are missing. Bias can be eliminated with parental data and can be reduced when additional markers not in LD are included in the analyses. |
format | Text |
id | pubmed-1866697 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-18666972007-05-11 Examining the effect of linkage disequilibrium on multipoint linkage analysis Huang, Qiqing Shete, Sanjay Swartz, Michael Amos, Christopher I BMC Genet Proceedings Most linkage programs assume linkage equilibrium among multiple linked markers. This assumption may lead to bias for tightly linked markers where strong linkage disequilibrium (LD) exists. We used simulated data from Genetic Analysis Workshop 14 to examine the possible effect of LD on multipoint linkage analysis. Single-nucleotide polymorphism packets from a non-disease-related region that was generated with LD were used for both model-free and parametric linkage analyses. Results showed that high LD among markers can induce false-positive evidence of linkage for affected sib-pair analysis when parental data are missing. Bias can be eliminated with parental data and can be reduced when additional markers not in LD are included in the analyses. BioMed Central 2005-12-30 /pmc/articles/PMC1866697/ /pubmed/16451698 http://dx.doi.org/10.1186/1471-2156-6-S1-S83 Text en Copyright © 2005 Huang 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 Huang, Qiqing Shete, Sanjay Swartz, Michael Amos, Christopher I Examining the effect of linkage disequilibrium on multipoint linkage analysis |
title | Examining the effect of linkage disequilibrium on multipoint linkage analysis |
title_full | Examining the effect of linkage disequilibrium on multipoint linkage analysis |
title_fullStr | Examining the effect of linkage disequilibrium on multipoint linkage analysis |
title_full_unstemmed | Examining the effect of linkage disequilibrium on multipoint linkage analysis |
title_short | Examining the effect of linkage disequilibrium on multipoint linkage analysis |
title_sort | examining the effect of linkage disequilibrium on multipoint linkage analysis |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866697/ https://www.ncbi.nlm.nih.gov/pubmed/16451698 http://dx.doi.org/10.1186/1471-2156-6-S1-S83 |
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