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Mixture distributions in human genetics research

Department of Genetics and Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, USA, The Jackson Laboratory, Bar Harbor, Maine, USA

David B Allison

Obesity Research Center, St Luke's Roosevelt Hospital, Columbia University, College of Physicians and Surgeons, New York, New York, USA

Bonnie Thiel

Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, USA

The use of mixture distributions in genetics research dates back to at least the late 1800s when Karl Pearson applied them in an analysis of crab morphometry. Pearson's use of normal mixture distributions to model the mixing of different species of crab (or 'families' of crab as he referred to them) within a defined geographic area motivated further use of mixture distributions in genetics research settings, and ultimately led to their development and recognition as intuitive modelling devices for the effects of underlying genes on quantitative phenotypic (i.e. trait) expression. In addition, mixture distributions are now used routinely to model or accommodate the genetic heterogeneity thought to underlie many human diseases. Specific applications of mixture distribution models in contemporary human genetics research are, in fact, too numerous to count. Despite this long, consistent and arguably illustrious history of use, little mention of mixture distributions in genetics research is made in many recent reviews on mixture models. This review attempts to rectify this by providing insight into the role that mixture distributions play in contemporary human genetics research. Tables providing examples from the litera ture that describe applications of mixture models in human genetics research are offered as a way of acquainting the interested reader with relevant studies. In addition, some of the more problematic aspects of the use of mixture models in genetics research are outlined and addressed.

Statistical Methods in Medical Research, Vol. 5, No. 2, 155-178 (1996)
DOI: 10.1177/096228029600500204


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