Simple and efficient analysis of disease association with missing genotype data.

Simple and efficient analysis of disease association with missing genotype data. Research Abstract Details 

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Simple and efficient analysis of disease association with missing genotype data. Abstract Text:

D Y Lin,Y Hu,B E Huang,D Y Lin,Y Hu,B E Huang,

Missing genotype data arise in association studies when the single-nucleotide polymorphisms (SNPs) on the genotying platform are not assayed successfully, when the SNPs of interest are not on the platform, or when total sequence variation is determined only on a small fraction of individuals. We present a simple and flexible likelihood framework to study SNP-disease associations with such missing genotype data. Our likelihood makes full use of all available data in case-control studies and reference panels (e.g., the HapMap), and it properly accounts for the biased nature of the case-control sampling as well as the uncertainty in inferring unknown variants. The corresponding maximum-likelihood estimators for genetic effects and gene-environment interactions are unbiased and statistically efficient. We developed fast and stable numerical algorithms to calculate the maximum-likelihood estimators and their variances, and we implemented these algorithms in a freely available computer program. Simulation studies demonstrated that the new approach is more powerful than existing methods while providing accurate control of the type I error. An application to a case-control study on rheumatoid arthritis revealed several loci that deserve further investigations.

Simple and efficient analysis of disease association with missing genotype data. Publishing Authors By Initials

DY Lin,Y Hu,BE Huang,DY Lin,Y Hu,BE Huang,

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Simple and efficient analysis of disease association with missing genotype data. Journal Published:

PUBLICATION TYPE: Journal Article

Journal: American journal of human genetics

VOLUME: 82

Page Numbers: 444-52

Journal Abbreviation: Am. J. Hum. Genet.

ISSN: 1537-6605

DAY: 6

MONTH: Feb

YEAR: 2008

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LANGUAGE: eng

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Grant and Affiliation Information for Simple and efficient analysis of disease association with missing genotype data.

AFFILIATION: Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7420, USA.

Country: United States

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MEDLINETA: Am J Hum Genet

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