A better coefficient of determination for genetic profile analysis

Lee, Sang Hong, Goddard, Michael E., Wray, Naomi R. and Visscher, Peter M. (2012) A better coefficient of determination for genetic profile analysis. Genetic Epidemiology, 36 3: 214-224. doi:10.1002/gepi.21614

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Author Lee, Sang Hong
Goddard, Michael E.
Wray, Naomi R.
Visscher, Peter M.
Title A better coefficient of determination for genetic profile analysis
Journal name Genetic Epidemiology   Check publisher's open access policy
ISSN 0741-0395
Publication date 2012-04
Sub-type Article (original research)
DOI 10.1002/gepi.21614
Open Access Status File (Author Post-print)
Volume 36
Issue 3
Start page 214
End page 224
Total pages 11
Place of publication Hoboken, NJ, United States
Publisher John Wiley & Sons
Collection year 2013
Language eng
Formatted abstract
Genome-wide association studies have facilitated the construction of risk predictors for disease from multiple Single Nucleotide Polymorphism markers. The ability of such “genetic profiles” to predict outcome is usually quantified in an independent data set. Coefficients of determination (R2) have been a useful measure to quantify the goodness-of-fit of the genetic profile. Various pseudo-R2 measures for binary responses have been proposed. However, there is no standard or consensus measure because the concept of residual variance is not easily defined on the observed probability scale. Unlike other nongenetic predictors such as environmental exposure, there is prior information on genetic predictors because for most traits there are estimates of the proportion of variation in risk in the population due to all genetic factors, the heritability. It is this useful ability to benchmark that makes the choice of a measure of goodness-of-fit in genetic profiling different from that of nongenetic predictors. In this study, we use a liability threshold model to establish the relationship between the observed probability scale and underlying liability scale in measuring R2 for binary responses. We show that currently used R2 measures are difficult to interpret, biased by ascertainment, and not comparable to heritability. We suggest a novel and globally standard measure of R2 that is interpretable on the liability scale. Furthermore, even when using ascertained case-control studies that are typical in human disease studies, we can obtain an R2 measure on the liability scale that can be compared directly to heritability.
Keyword Coefficient of determination
Risk predictors
Genetic profiles
Genome-wide association studies
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Queensland Brain Institute Publications
Official 2013 Collection
UQ Diamantina Institute Publications
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Citation counts: TR Web of Science Citation Count  Cited 22 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 22 times in Scopus Article | Citations
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