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

被引:2
|
作者
Cooper, Matthew N. [1 ]
de Klerk, Nicholas H. [1 ]
Greenop, Kathryn R. [1 ]
Jamieson, Sarra E. [1 ]
Anderson, Denise [1 ]
van Bockxmeer, Frank M. [2 ]
Armstrong, Bruce K. [3 ]
Milne, Elizabeth [1 ]
机构
[1] Univ Western Australia, Ctr Child Hlth Res, Telethon Inst Child Hlth Res, Perth, WA 6872, Australia
[2] Univ Western Australia, Royal Perth Hosp, Sch Pathol & Lab Med, Crawley, WA, Australia
[3] Univ Sydney, Sydney Sch Publ Hlth, Camperdown, NSW, Australia
基金
澳大利亚国家健康与医学研究理事会; 英国医学研究理事会;
关键词
Biostatistics; DNA; Genotype; Measurement error; Quality control; Whole genome amplification;
D O I
10.1186/1471-2288-12-141
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: Genotyping 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. Methods: Discordance 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. Results: Application 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. Conclusions: Bias 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.
引用
收藏
页数:8
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