Document Detail


Quantitative trait prediction based on genetic marker-array data, a simulation study.
MedLine Citation:
PMID:  21285022     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
MOTIVATION: Using simulation studies for quantitative trait loci (QTL), we evaluate the prediction quality of regression models that include as covariates single-nucleotide polymorphism (SNP) genetic markers which did not achieve genome-wide significance in the original genome-wide association study, but were among the SNPs with the smallest P-value for the selected association test. We compare the results of such regression models to the standard approach which is to include only SNPs that achieve genome-wide significance. Using mean square prediction error as the model metric, our simulation results suggest that by using the coefficient of determination (R(2)) value as a guideline to increase or reduce the number of SNPs included in the regression model, we can achieve better prediction quality than the standard approach. However, important parameters such as trait heritability, the approximate number of QTLs, etc. have to be determined from previous studies or have to be estimated accurately.
Authors:
Wai-Ki Yip; Christoph Lange
Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural     Date:  2011-01-31
Journal Detail:
Title:  Bioinformatics (Oxford, England)     Volume:  27     ISSN:  1367-4811     ISO Abbreviation:  Bioinformatics     Publication Date:  2011 Mar 
Date Detail:
Created Date:  2011-03-10     Completed Date:  2011-05-31     Revised Date:  2012-10-09    
Medline Journal Info:
Nlm Unique ID:  9808944     Medline TA:  Bioinformatics     Country:  England    
Other Details:
Languages:  eng     Pagination:  745-8     Citation Subset:  IM    
Affiliation:
Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. wkyip@hsph.harvard.edu
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MeSH Terms
Descriptor/Qualifier:
Chromosome Mapping / methods
Computer Simulation
Genetic Markers
Genome-Wide Association Study
Genotype
Humans
Inheritance Patterns
Models, Genetic*
Phenotype
Polymorphism, Single Nucleotide*
Quantitative Trait Loci*
Regression Analysis
Grant Support
ID/Acronym/Agency:
R01 MH087590/MH/NIMH NIH HHS; R01 MH087590-03/MH/NIMH NIH HHS; R01MH081862/MH/NIMH NIH HHS; R01MH087590/MH/NIMH NIH HHS
Chemical
Reg. No./Substance:
0/Genetic Markers
Comments/Corrections

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