Statistical inference for Hardy-Weinberg proportions in the presence of missing genotype information
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10.1371/journal.pone.0083316
Inclou dades d'ús des de 2022
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hdl:2117/21263
Tipus de documentArticle
Data publicació2013-12-31
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Abstract
In genetic association studies, tests for Hardy-Weinberg proportions are often employed as a quality control checking
procedure. Missing genotypes are typically discarded prior to testing. In this paper we show that inference for Hardy-
Weinberg proportions can be biased when missing values are discarded. We propose to use multiple imputation of missing
values in order to improve inference for Hardy-Weinberg proportions. For imputation we employ a multinomial logit model
that uses information from allele intensities and/or neighbouring markers. Analysis of an empirical data set of single
nucleotide polymorphisms possibly related to colon cancer reveals that missing genotypes are not missing completely at
random. Deviation from Hardy-Weinberg proportions is mostly due to a lack of heterozygotes. Inbreeding coefficients
estimated by multiple imputation of the missings are typically lowered with respect to inbreeding coefficients estimated by
discarding the missings. Accounting for missings by multiple imputation qualitatively changed the results of 10 to 17% of
the statistical tests performed. Estimates of inbreeding coefficients obtained by multiple imputation showed high
correlation with estimates obtained by single imputation using an external reference panel. Our conclusion is that
imputation of missing data leads to improved statistical inference for Hardy-Weinberg proportions
CitacióGraffelman, J. [et al.]. Statistical inference for Hardy-Weinberg proportions in the presence of missing genotype information. "PLoS One", 31 Desembre 2013, vol. 8, núm. 12, p. 1-11.
ISSN1932-6203
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