Results: 3

1.
Figure 1

Figure 1. From: How accurate can genetic predictions be?.

Example risk distribution. This distribution has a prevalence of 30% and a heritability of 10%. The mean of the distribution equals the prevalence of the trait. Variance represents the variance of risk due to genetic variation, sometimes called genetic variance, and is proportional to heritability.

Jonathan M Dreyfuss, et al. BMC Genomics. 2012;13:340-340.
2.
Figure 2

Figure 2. From: How accurate can genetic predictions be?.

Heritability vs. predictive accuracy. Relationship of heritability (computed on the observed binary scale) or proportion of variance explained to the maximal upper limit on AUC. The numbers next to the curves represent the prevalence. The maximal AUCs are compared with those that would exist if the genetic risk distribution followed a beta distribution, which is consistent with previous reports [10,12,13].

Jonathan M Dreyfuss, et al. BMC Genomics. 2012;13:340-340.
3.
Figure 3

Figure 3. From: How accurate can genetic predictions be?.

ROC curves for type 2 diabetes and breast cancer from genomic profiles. Maximal sensitivity / 1-specificity pairs for prediction of type 2 diabetes and breast cancer from full genomic profiles. The maximal pairs are compared to the pairs that would exist if the genetic risk distribution followed a beta distribution, which is consistent with previous reports [10,12,13].

Jonathan M Dreyfuss, et al. BMC Genomics. 2012;13:340-340.

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