The relationship between imputation error and statistical power in genetic association studies in diverse populations

scientific article published on 22 October 2009

The relationship between imputation error and statistical power in genetic association studies in diverse populations is …
instance of (P31):
scholarly articleQ13442814

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P356DOI10.1016/J.AJHG.2009.09.017
P932PMC publication ID2775841
P698PubMed publication ID19853241
P5875ResearchGate publication ID38032705

P50authorNoah RosenbergQ7045447
P2093author name stringChaolong Wang
Lucy Huang
P2860cites workA flexible and accurate genotype imputation method for the next generation of genome-wide association studiesQ21129496
Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's diseaseQ22251069
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A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individualsQ24644474
Newly identified loci that influence lipid concentrations and risk of coronary artery diseaseQ28264535
Identification of ten loci associated with height highlights new biological pathways in human growthQ28275237
Practical aspects of imputation-driven meta-analysis of genome-wide association studiesQ28749837
Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetesQ29417138
A new multipoint method for genome-wide association studies by imputation of genotypesQ29547209
A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variantsQ29547210
Genotype, haplotype and copy-number variation in worldwide human populationsQ29615885
Linkage disequilibrium in humans: models and dataQ30654298
Imputation-based analysis of association studies: candidate regions and quantitative traitsQ30833155
Methods to impute missing genotypes for population dataQ33298732
Missing data imputation and haplotype phase inference for genome-wide association studiesQ33375386
Analyses and comparison of accuracy of different genotype imputation methodsQ33380176
Practical issues in imputation-based association mappingQ33389849
Imputation of missing genotypes: an empirical evaluation of IMPUTE.Q33392479
A comprehensive evaluation of SNP genotype imputationQ34906095
Using population mixtures to optimize the utility of genomic databases: linkage disequilibrium and association study design in IndiaQ36808806
Genotype-imputation accuracy across worldwide human populationsQ37156125
Genome-wide association studies: implications for multiethnic samplesQ37292889
Evaluation of potential power gain with imputed genotypes in genome-wide association studiesQ39990503
A worldwide survey of haplotype variation and linkage disequilibrium in the human genomeQ42601487
Power and sample size calculations for case-control genetic association tests when errors are present: application to single nucleotide polymorphismsQ47175186
Testing untyped alleles (TUNA)-applications to genome-wide association studies.Q51933120
What SNP genotyping errors are most costly for genetic association studies?Q52004489
P433issue5
P407language of work or nameEnglishQ1860
P921main subjectstatisticsQ12483
imputationQ1660484
P304page(s)692-698
P577publication date2009-10-22
P1433published inAmerican Journal of Human GeneticsQ4744249
P1476titleThe relationship between imputation error and statistical power in genetic association studies in diverse populations
P478volume85

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