Evidence map›Paper›PMID 22970889›Full record

ArticleBMC medical research methodology2012

Statistical adjustment of genotyping error in a case-control study of childhood leukaemia.

Matthew N Cooper, Nicholas H de Klerk, Kathryn R Greenop, Sarra E Jamieson, Denise Anderson, Frank M van Bockxmeer, Bruce K Armstrong, Elizabeth Milne

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Article in BMC medical research methodology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Matthew N CooperTelethon Institute for Child Health Research, Centre for Child Health Research, University of Western Australia, West Perth, 6872, WA, Australia. mcooper@ichr.uwa.edu.au
Nicholas H de Klerk
Kathryn R Greenop
Sarra E Jamieson
Denise Anderson
Frank M van Bockxmeer
Bruce K Armstrong
Elizabeth Milne

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenotyping has become more cost-effective and less invasive with the use of buccal cell sampling. However, low or fragmented DNA yields from buccal cells collected using FTA cards often requires additional whole genome amplification to produce sufficient DNA for genotyping. In our case-control study of childhood leukaemia, discordance was found between genotypes derived from blood and whole genome amplified FTA buccal DNA samples. We aimed to develop a user-friendly method to correct for this genotype misclassification, as existing methods were not suitable for use in our study.

methodsDiscordance between the results of blood and buccal-derived DNA was assessed in childhood leukaemia cases who had both blood and FTA buccal samples. A method based on applying misclassification probabilities to measured data and combining results using multiple imputations, was devised to correct for error in the genotypes of control subjects, for whom only buccal samples were available, to minimize bias in the odds ratios in the case-control analysis.

resultsApplication of the correction method to synthetic datasets showed it was effective in producing correct odds ratios from data with known misclassification. Moreover, when applied to each of six bi-allelic loci, correction altered the odds ratios in the logically anticipated manner given the degree and direction of the misclassification revealed by the investigations in cases. The precision of the effect estimates decreased with decreasing size of the misclassification data set.

conclusionsBias arising from differential genotype misclassification can be reduced by correcting results using this method whenever data on concordance of genotyping results with those from a different and probably better DNA source are available.

Indexed as

Case-Control StudiesChildDiagnostic ErrorsDNADNA FingerprintingFemaleGenetic VariationGenotyping TechniquesHumansLeukemiaMaleReagent Kits, DiagnosticDNAReagent Kits, Diagnostic

Identifiers

PMID22970889
PMCPMC3514307

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