<p>ROC curves depicting the performance of a random forest classifier to predict within cell type reproducibility (red), between cell type reproducibility (blue), and within cell type specific reproducibility (green). Predictions plotted separately for (A) LCL/LCL/Liver, (B)Liver/Liver/LCL, and (C) Brain/Brain/LCL. The classifier was trained on a diverse collection of CREs (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003649#s4" target="_blank">Methods</a> and Supplement for complete data set description). True positive rates (y-axis) and false positive rates (x-axis) were quantified by ten fold cross validation.</p
<p>The bar plots correspond to the average area under the ROC curve obtained from five widely used s...
<p>Our approach is designed to generate reliable and relevant predictive biological networks using h...
Expression quantitative trait loci (eQTL) can reveal the regulatory mechanisms of trait associated v...
<p>(A) Prediction performances on hold-out chromatin factor profiles based on partial data and chrom...
<p>(A, B, C) eQTL replication frequency (y-axis) as a function of discovery significance (x-axis: )....
<p>Classification performance was measured as area under the curve (AUC) of the ROC curve. A perfect...
<p>Each row represents a clinical phenotype and consists of 130 cells, each of which represents a Pe...
<p>(A) Heatmap representation of the matrix of association statistics (chi-squared scores) from one-...
(A) ROC curves for simulated whole-exome sequencing data, for one cancer type versus all others. Are...
<p>Area under the 5-fold cross-validated ROC curve decreases with increase in number of trees stabil...
<p>ROC curve of random forest classification in liver of: <b>a</b>) genotoxicity and <b>b</b>) carci...
<p>A.)Validation Rate in the 12 cell-types measured by overlap with DNase-I HS, B.)Misclassification...
<p>(A) The ROC curves for 3 classification models that use TF-only, motif-only features or a combina...
<p>Within macro-dissected brain tissue samples, variable cell type balance is likely to influence th...
<p>A) Individual cell analysis- training sets were built from manually-cropped single cells. An exam...
<p>The bar plots correspond to the average area under the ROC curve obtained from five widely used s...
<p>Our approach is designed to generate reliable and relevant predictive biological networks using h...
Expression quantitative trait loci (eQTL) can reveal the regulatory mechanisms of trait associated v...
<p>(A) Prediction performances on hold-out chromatin factor profiles based on partial data and chrom...
<p>(A, B, C) eQTL replication frequency (y-axis) as a function of discovery significance (x-axis: )....
<p>Classification performance was measured as area under the curve (AUC) of the ROC curve. A perfect...
<p>Each row represents a clinical phenotype and consists of 130 cells, each of which represents a Pe...
<p>(A) Heatmap representation of the matrix of association statistics (chi-squared scores) from one-...
(A) ROC curves for simulated whole-exome sequencing data, for one cancer type versus all others. Are...
<p>Area under the 5-fold cross-validated ROC curve decreases with increase in number of trees stabil...
<p>ROC curve of random forest classification in liver of: <b>a</b>) genotoxicity and <b>b</b>) carci...
<p>A.)Validation Rate in the 12 cell-types measured by overlap with DNase-I HS, B.)Misclassification...
<p>(A) The ROC curves for 3 classification models that use TF-only, motif-only features or a combina...
<p>Within macro-dissected brain tissue samples, variable cell type balance is likely to influence th...
<p>A) Individual cell analysis- training sets were built from manually-cropped single cells. An exam...
<p>The bar plots correspond to the average area under the ROC curve obtained from five widely used s...
<p>Our approach is designed to generate reliable and relevant predictive biological networks using h...
Expression quantitative trait loci (eQTL) can reveal the regulatory mechanisms of trait associated v...