Fig. 4

XCI status predictions with an epigenetic model expands the number of genes examinable. a ROC curves for each random forest predictor trained using single marks, along with the combined predictor using all of the epigenetic marks. An example sample, CEMT28 is shown. See Additional file 1: Figure S8 for all samples. b Accuracy of our epigenetic predictor using DNAme and all six histone marks. Each point is one of the 20 models per sample. This accuracy is tested on genes outside of the training set. c The number of genes with each XCI status as predicted by our model, with their call by meta-status underneath. d, e As (c), but further split by the presence of a CpG island (d) or by an expression threshold of 0.1 RPKM (e). f The predictive ability of each mark. Each mark was ranked per model on how important it was to the model, with the most important mark being ranked 14 and the least important being ranked first. We used the marks within each female sample paired with the mean mark in similar male samples for the predictor, so both the female and male marks are featured here