Literature DB >> 16612103

Effects of differential genotyping error rate on the type I error probability of case-control studies.

Valentina Moskvina1, Nick Craddock, Peter Holmans, Michael J Owen, Michael C O'Donovan.   

Abstract

OBJECTIVES: It is well known that genotyping error adversely affects the power of genetic case-control association studies but there is little research on its effects on type I error, and none that has addressed possible differences in genotype error rates between cases and controls.
METHODS: We used simulations to examine the influence of genotyping error on the type I error probability given by case-control studies. The effect of genotyping error on the magnitude of type I error was explored for a single marker of varying minor allele frequency (MAF), and for haplotypic tests based on two markers with varying MAF and linkage disequilibrium (LD) measure r(2).
RESULTS: We show that even with low genotyping error rates (<0.01), systematic differences in the error rate between samples can result in type I error rates substantially above 0.05. The effect was maximal for markers with small MAF, markers in strong LD, and where a common allele is more frequently misclassified as a rare allele than vice versa. The problem was also exacerbated by the use of large samples.
CONCLUSIONS: Our results show that small differential genotyping error rates between cases and controls pose significant problems for association analyses. Differential genotyping error rates are particularly likely to arise where genotype data are combined from multiple sites, or where case genotypes are examined against archived reference population cohort genotypes that are being generated in several countries. Although these strategies may be necessary to obtain adequately powered samples, our data show the importance of stringent quality control. Furthermore, associations based on rare haplotypes should be treated with caution.

Mesh:

Year:  2006        PMID: 16612103     DOI: 10.1159/000092553

Source DB:  PubMed          Journal:  Hum Hered        ISSN: 0001-5652            Impact factor:   0.444


  38 in total

1.  Assessing the impact of non-differential genotyping errors on rare variant tests of association.

Authors:  Scott Powers; Shyam Gopalakrishnan; Nathan Tintle
Journal:  Hum Hered       Date:  2011-10-15       Impact factor: 0.444

2.  Spoiling the whole bunch: quality control aimed at preserving the integrity of high-throughput genotyping.

Authors:  Anna Pluzhnikov; Jennifer E Below; Anuar Konkashbaev; Anna Tikhomirov; Emily Kistner-Griffin; Cheryl A Roe; Dan L Nicolae; Nancy J Cox
Journal:  Am J Hum Genet       Date:  2010-07-09       Impact factor: 11.025

3.  Evaluating variations of genotype calling: a potential source of spurious associations in genome-wide association studies.

Authors:  Huixiao Hong; Zhenqiang Su; Weigong Ge; Leming Shi; Roger Perkins; Hong Fang; Donna Mendrick; Weida Tong
Journal:  J Genet       Date:  2010-04       Impact factor: 1.166

4.  Smarter clustering methods for SNP genotype calling.

Authors:  Yan Lin; George C Tseng; Soo Yeon Cheong; Lora J H Bean; Stephanie L Sherman; Eleanor Feingold
Journal:  Bioinformatics       Date:  2008-09-29       Impact factor: 6.937

Review 5.  A HapMap harvest of insights into the genetics of common disease.

Authors:  Teri A Manolio; Lisa D Brooks; Francis S Collins
Journal:  J Clin Invest       Date:  2008-05       Impact factor: 14.808

6.  Simultaneously correcting for population stratification and for genotyping error in case-control association studies.

Authors:  K F Cheng; W J Lin
Journal:  Am J Hum Genet       Date:  2007-08-22       Impact factor: 11.025

7.  Genotyping error detection in samples of unrelated individuals without replicate genotyping.

Authors:  Nianjun Liu; Dabao Zhang; Hongyu Zhao
Journal:  Hum Hered       Date:  2008-12-15       Impact factor: 0.444

8.  The effect of minor allele frequency on the likelihood of obtaining false positives.

Authors:  Meredith E Tabangin; Jessica G Woo; Lisa J Martin
Journal:  BMC Proc       Date:  2009-12-15

9.  Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease.

Authors:  Denise Harold; Richard Abraham; Paul Hollingworth; Rebecca Sims; Amy Gerrish; Marian L Hamshere; Jaspreet Singh Pahwa; Valentina Moskvina; Kimberley Dowzell; Amy Williams; Nicola Jones; Charlene Thomas; Alexandra Stretton; Angharad R Morgan; Simon Lovestone; John Powell; Petroula Proitsi; Michelle K Lupton; Carol Brayne; David C Rubinsztein; Michael Gill; Brian Lawlor; Aoibhinn Lynch; Kevin Morgan; Kristelle S Brown; Peter A Passmore; David Craig; Bernadette McGuinness; Stephen Todd; Clive Holmes; David Mann; A David Smith; Seth Love; Patrick G Kehoe; John Hardy; Simon Mead; Nick Fox; Martin Rossor; John Collinge; Wolfgang Maier; Frank Jessen; Britta Schürmann; Reinhard Heun; Hendrik van den Bussche; Isabella Heuser; Johannes Kornhuber; Jens Wiltfang; Martin Dichgans; Lutz Frölich; Harald Hampel; Michael Hüll; Dan Rujescu; Alison M Goate; John S K Kauwe; Carlos Cruchaga; Petra Nowotny; John C Morris; Kevin Mayo; Kristel Sleegers; Karolien Bettens; Sebastiaan Engelborghs; Peter P De Deyn; Christine Van Broeckhoven; Gill Livingston; Nicholas J Bass; Hugh Gurling; Andrew McQuillin; Rhian Gwilliam; Panagiotis Deloukas; Ammar Al-Chalabi; Christopher E Shaw; Magda Tsolaki; Andrew B Singleton; Rita Guerreiro; Thomas W Mühleisen; Markus M Nöthen; Susanne Moebus; Karl-Heinz Jöckel; Norman Klopp; H-Erich Wichmann; Minerva M Carrasquillo; V Shane Pankratz; Steven G Younkin; Peter A Holmans; Michael O'Donovan; Michael J Owen; Julie Williams
Journal:  Nat Genet       Date:  2009-09-06       Impact factor: 38.330

10.  Assessing the utility of whole-genome amplified serum DNA for array-based high throughput genotyping.

Authors:  Kristine L Bucasas; Gagan A Pandya; Sonal Pradhan; Robert D Fleischmann; Scott N Peterson; John W Belmont
Journal:  BMC Genet       Date:  2009-12-18       Impact factor: 2.797

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