Incorporating Duplicate Genotype Data into Linear Trend Tests of Genetic Association: Methods and Cost-Effectiveness

Borchers Bryce, Brown Marshall, McLellan Brian, Bekmetjev Airat and Tintle Nathan L
Additional contact information
Borchers Bryce: Rose-Hulman Institute of Technology
Brown Marshall: Seattle Pacific University
McLellan Brian: Hope College
Bekmetjev Airat: Hope College
Tintle Nathan L: Hope College

Statistical Applications in Genetics and Molecular Biology, 2009, vol. 8, issue 1, 22

Abstract: The genome-wide association (GWA) study is an increasingly popular way to attempt to identify the causal variants in human disease. Duplicate genotyping (or re-genotyping) a portion of the samples in a GWA study is common, though it is typical for these data to be ignored in subsequent tests of genetic association. We demonstrate a method for including duplicate genotype data in linear trend tests of genetic association which yields increased power. We also consider the cost-effectiveness of collecting duplicate genotype data and find that when the relative cost of genotyping to phenotyping and sample acquisition costs is less than or equal to the genotyping error rate it is more powerful to duplicate genotype the entire sample instead of spending the same money to increase the sample size. Duplicate genotyping is particularly cost-effective when SNP minor allele frequencies are low. Practical advice for the implementation of duplicate genotyping is provided. Free software is provided to compute asymptotic and permutation based tests of association using duplicate genotype data as well as to aid in the duplicate genotyping design decision.

Keywords: re-genotype; genome-wide association; genotyping error; genotype error; SNP (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (1)

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DOI: 10.2202/1544-6115.1433

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