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A quantitative trait linkage method ...
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Xu, Zhiying.
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A quantitative trait linkage method for longitudinal pedigree data and its application.
Record Type:
Electronic resources : Monograph/item
Title/Author:
A quantitative trait linkage method for longitudinal pedigree data and its application./
Author:
Xu, Zhiying.
Description:
107 p.
Notes:
Source: Dissertation Abstracts International, Volume: 67-08, Section: B, page: 4191.
Contained By:
Dissertation Abstracts International67-08B.
Subject:
Biology, Biostatistics. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3233108
ISBN:
9780542856327
A quantitative trait linkage method for longitudinal pedigree data and its application.
Xu, Zhiying.
A quantitative trait linkage method for longitudinal pedigree data and its application.
- 107 p.
Source: Dissertation Abstracts International, Volume: 67-08, Section: B, page: 4191.
Thesis (Ph.D.)--Case Western Reserve University, 2007.
In the past decade, availability of longitudinal genetic data made possible the investigation of genetic and environmental factors that influence long-term average and changes over time in a complex trait. However we are lacking of a powerful statistical method to better understand these data. In this dissertation, a generalized mixed model based on the Haseman-Elston regression framework to discover genetic variation over time (major gene vs. slope gene) was thoroughly studied. The proposed model allows for different genetic random effects and different covariance structures for pedigree data to examine the change over time effect. Models with sibship cross product (rHE), sibship sample mean corrected cross product (smHE) and BLUP-mean corrected cross product (pmHE) as response variables were evaluated by simulation studies. The GAW13 cohort 2 simulation data was used to compute the power and type I error rate for each scenario. We concluded that the mixed model with both family and sibpair random effects performs well with average type I error rate at around 0.05 and average power over 70% at nominal level of 0.05 when response variable is smHE or pmHE. In addition, the proposed model was successfully applied to the Beaver Dam Eye Study (BDES) to detect association between progression of multiple age-related maculopathy traits and susceptible genes.
ISBN: 9780542856327Subjects--Topical Terms:
1018416
Biology, Biostatistics.
A quantitative trait linkage method for longitudinal pedigree data and its application.
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A quantitative trait linkage method for longitudinal pedigree data and its application.
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Source: Dissertation Abstracts International, Volume: 67-08, Section: B, page: 4191.
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Adviser: Sudha K. Iyengar.
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Thesis (Ph.D.)--Case Western Reserve University, 2007.
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In the past decade, availability of longitudinal genetic data made possible the investigation of genetic and environmental factors that influence long-term average and changes over time in a complex trait. However we are lacking of a powerful statistical method to better understand these data. In this dissertation, a generalized mixed model based on the Haseman-Elston regression framework to discover genetic variation over time (major gene vs. slope gene) was thoroughly studied. The proposed model allows for different genetic random effects and different covariance structures for pedigree data to examine the change over time effect. Models with sibship cross product (rHE), sibship sample mean corrected cross product (smHE) and BLUP-mean corrected cross product (pmHE) as response variables were evaluated by simulation studies. The GAW13 cohort 2 simulation data was used to compute the power and type I error rate for each scenario. We concluded that the mixed model with both family and sibpair random effects performs well with average type I error rate at around 0.05 and average power over 70% at nominal level of 0.05 when response variable is smHE or pmHE. In addition, the proposed model was successfully applied to the Beaver Dam Eye Study (BDES) to detect association between progression of multiple age-related maculopathy traits and susceptible genes.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3233108
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