Plots showing the mean and standard deviation accuracy of sex prediction on two external datasets using a predictor trained using different sample sizes from our dataset.

<p>We built predictors using different training sample sizes ranging from n = 10 (5♀, 5♂) to n = 110 (55♀, 55♂) from our full dataset. We then calculated the prediction accuracy, for each n ( = 10…110) on two external datasets (A. Dataset GSE24215 and B. Dataset GSE23697). This was repeated 50 times and the mean and standard deviation prediction accuracy for each sample size was calculated. As the training sample size increased, so did prediction accuracy on the external datasets.</p

Patient characteristics.

*<p>Different from men, p-value <0.0001.</p>1<p>Derived regression equations <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065380#pone.0065380-Shen1" target="_blank">[19]</a>.</p

Box-and-whiskers plot showing the mean internal cross-validation accuracy of sex prediction for different sample sizes.

<p>Sample sizes tested ranged from n = 10 (5♀, 5♂) to n = 110 (55♀, 55♂). To calculate the mean 10-fold cross validation prediction accuracy, for each n ( = 10…110), we built classification models using a randomly selected size-n subsamples of our full dataset of n = 134. This was repeated 50 times and the median prediction accuracy for each sample was calculated. As sample size increased, so did prediction accuracy.</p