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. 2009 Jul;5(7):e1000540.
doi: 10.1371/journal.pgen.1000540. Epub 2009 Jul 3.

Prediction and interaction in complex disease genetics: experience in type 1 diabetes

David G Clayton  1
Affiliations

Prediction and interaction in complex disease genetics: experience in type 1 diabetes

David G Clayton. PLoS Genet. 2009 Jul.
No abstract available

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Conflict of interest statement

The author has declared that no competing interests exist.

Figures

Figure 1
Figure 1. ROC curve for the prediction score of Truett, Cornfield, and Kannel (five-year incidence of coronary heart disease in the Framingham cohort study).
Figure 2
Figure 2. Theoretical ROC curves for various values of λs under the polygenic multiplicative model.
Figure 3
Figure 3. ROC curves prediction from loci in the MHC region.
Prediction using six single nucleotide polymorphisms (SNPs) is shown in red, while prediction using HLA-DRB1 is shown in green. These curves (and those in Figures 4 and 5) were obtained by fitting logistic regression models as described in Text S1 and calculating the proportions of cases and controls with prediction scores exceeding each possible value. The dashed curve corresponds to the theoretical curve for the polygenic multiplicative model with λs = 3.13.
Figure 4
Figure 4. ROC curve prediction from the SNPs outside the MHC region listed in Supplementary Table 1 in Text S1 (in blue).
The dashed curve corresponds to a polygenic multiplicative model with λs = 1.48.
Figure 5
Figure 5. ROC curve prediction from all the SNPs listed in Supplementary Table 1 in Text S1 (in blue).
The prediction curve using the six MHC SNPs alone is shown in red, and the dashed curve corresponds to a polygenic multiplicative model with λs = 4.75.
See this image and copyright information in PMC

References

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