Document Detail


Association tests for X-chromosomal markers--a comparison of different test statistics.
MedLine Citation:
PMID:  21325864     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
OBJECTIVE: Genome-wide association studies have successfully elucidated the genetic background of complex diseases, but X chromosomal data have usually not been analyzed. A reason for this is that there is no consensus approach for the analysis taking into account the specific features of X chromosomal data. This contribution evaluates test statistics proposed for X chromosomal markers regarding type I error frequencies and power.
METHODS: We performed extensive simulation studies covering a wide range of different settings. Besides characteristics of the general population, we investigated sex-balanced or unbalanced sampling procedures as well as sex-specific effect sizes, allele frequencies and prevalence. Finally, we applied the test statistics to an association data set on Crohn's disease.
RESULTS: Simulation results imply that in addition to standard quality control, sex-specific allele frequencies should be checked to control for type I errors. Furthermore, we observed distinct differences in power between test statistics which are determined by sampling design and sex specificity of effect sizes. Analysis of the Crohn's disease data detects two previously unknown genetic regions on the X chromosome.
CONCLUSION: Although no test is uniformly most powerful under all settings, recommendations are offered as to which test performs best under certain conditions.
Authors:
Christina Loley; Andreas Ziegler; Inke R König
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Publication Detail:
Type:  Comparative Study; Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't     Date:  2011-02-16
Journal Detail:
Title:  Human heredity     Volume:  71     ISSN:  1423-0062     ISO Abbreviation:  Hum. Hered.     Publication Date:  2011  
Date Detail:
Created Date:  2011-04-21     Completed Date:  2011-08-04     Revised Date:  2013-06-30    
Medline Journal Info:
Nlm Unique ID:  0200525     Medline TA:  Hum Hered     Country:  Switzerland    
Other Details:
Languages:  eng     Pagination:  23-36     Citation Subset:  IM    
Copyright Information:
Copyright © 2011 S. Karger AG, Basel.
Affiliation:
Institut für Medizinische Biometrie und Statistik, Universität zu Lübeck, Lübeck, Deutschland.
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Alleles
Case-Control Studies
Chromosomes, Human, X / genetics*
Computer Simulation
Crohn Disease / genetics
Data Interpretation, Statistical*
Female
Gene Frequency
Genetic Markers
Genetic Predisposition to Disease
Genome-Wide Association Study*
Genotype
Humans
Linkage Disequilibrium
Male
Models, Genetic
Polymorphism, Single Nucleotide / genetics
Sex Factors
Chemical
Reg. No./Substance:
0/Genetic Markers
Comments/Corrections

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