Joint modeling of genetic linkage and association

Understanding the complexities involved in identifying disease causing genes is still a monumental task. As we know, genetic variants and environmental factors can influence the risk of disease outcomes. Epidemiological studies have identified that age is one of a number of environmental risk factor...

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Main Author: Yang, Haiyan
Format: Thesis
Language:English
Published: Memorial University of Newfoundland 2014
Subjects:
Online Access:https://research.library.mun.ca/6404/
https://research.library.mun.ca/6404/1/PhDthesis_Haiyan.pdf
https://research.library.mun.ca/6404/3/PhDthesis_Haiyan.pdf
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spelling ftmemorialuniv:oai:research.library.mun.ca:6404 2023-10-01T03:57:38+02:00 Joint modeling of genetic linkage and association Yang, Haiyan 2014-05 application/pdf https://research.library.mun.ca/6404/ https://research.library.mun.ca/6404/1/PhDthesis_Haiyan.pdf https://research.library.mun.ca/6404/3/PhDthesis_Haiyan.pdf en eng Memorial University of Newfoundland https://research.library.mun.ca/6404/1/PhDthesis_Haiyan.pdf https://research.library.mun.ca/6404/3/PhDthesis_Haiyan.pdf Yang, Haiyan <https://research.library.mun.ca/view/creator_az/Yang=3AHaiyan=3A=3A.html> (2014) Joint modeling of genetic linkage and association. Doctoral (PhD) thesis, Memorial University of Newfoundland. thesis_license Thesis NonPeerReviewed 2014 ftmemorialuniv 2023-09-03T06:45:50Z Understanding the complexities involved in identifying disease causing genes is still a monumental task. As we know, genetic variants and environmental factors can influence the risk of disease outcomes. Epidemiological studies have identified that age is one of a number of environmental risk factors for Familial Pulmonary Fibrosis (FPF), but the genetic risk factors involved identification of disease causing genes still are a problem largely unsolved. An inherited disease-causing locus occurs in the same genomic position as an ancestor who has the disease trait, and the disease genotype may be associated with a marker genotype. A joint modeling of genetic linkage and association within families having a remote common ancestor or at population level is presented in this thesis. This joint modeling uses a likelihood approach that allows the inclusion of other covariates into the model for quantitative traits and binary traits with multivariate random effects. Power studies via simulation compare the new proposed procedure with standard linkage or association procedures. The joint test is more powerful than linkage or association test alone where both sources of variation of linkage or association are present. Furthermore, the proposed method also allows testing against specific alternatives - for example, against the significance of linkage where there is no association, significance of association where there is no linkage, and significance of both linkage and association. By utilizing data from five FPF families in Newfoundland, four candidate loci were identified for the linkage or/and association with age-at-onset gene and FPF (rs4605929 in chromosome 6, rs11078200 in chromosome 7, rs1941686 in chromosome 18 and rs114682 in chromosome 22). Thesis Newfoundland Memorial University of Newfoundland: Research Repository
institution Open Polar
collection Memorial University of Newfoundland: Research Repository
op_collection_id ftmemorialuniv
language English
description Understanding the complexities involved in identifying disease causing genes is still a monumental task. As we know, genetic variants and environmental factors can influence the risk of disease outcomes. Epidemiological studies have identified that age is one of a number of environmental risk factors for Familial Pulmonary Fibrosis (FPF), but the genetic risk factors involved identification of disease causing genes still are a problem largely unsolved. An inherited disease-causing locus occurs in the same genomic position as an ancestor who has the disease trait, and the disease genotype may be associated with a marker genotype. A joint modeling of genetic linkage and association within families having a remote common ancestor or at population level is presented in this thesis. This joint modeling uses a likelihood approach that allows the inclusion of other covariates into the model for quantitative traits and binary traits with multivariate random effects. Power studies via simulation compare the new proposed procedure with standard linkage or association procedures. The joint test is more powerful than linkage or association test alone where both sources of variation of linkage or association are present. Furthermore, the proposed method also allows testing against specific alternatives - for example, against the significance of linkage where there is no association, significance of association where there is no linkage, and significance of both linkage and association. By utilizing data from five FPF families in Newfoundland, four candidate loci were identified for the linkage or/and association with age-at-onset gene and FPF (rs4605929 in chromosome 6, rs11078200 in chromosome 7, rs1941686 in chromosome 18 and rs114682 in chromosome 22).
format Thesis
author Yang, Haiyan
spellingShingle Yang, Haiyan
Joint modeling of genetic linkage and association
author_facet Yang, Haiyan
author_sort Yang, Haiyan
title Joint modeling of genetic linkage and association
title_short Joint modeling of genetic linkage and association
title_full Joint modeling of genetic linkage and association
title_fullStr Joint modeling of genetic linkage and association
title_full_unstemmed Joint modeling of genetic linkage and association
title_sort joint modeling of genetic linkage and association
publisher Memorial University of Newfoundland
publishDate 2014
url https://research.library.mun.ca/6404/
https://research.library.mun.ca/6404/1/PhDthesis_Haiyan.pdf
https://research.library.mun.ca/6404/3/PhDthesis_Haiyan.pdf
genre Newfoundland
genre_facet Newfoundland
op_relation https://research.library.mun.ca/6404/1/PhDthesis_Haiyan.pdf
https://research.library.mun.ca/6404/3/PhDthesis_Haiyan.pdf
Yang, Haiyan <https://research.library.mun.ca/view/creator_az/Yang=3AHaiyan=3A=3A.html> (2014) Joint modeling of genetic linkage and association. Doctoral (PhD) thesis, Memorial University of Newfoundland.
op_rights thesis_license
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