Calculates area under the ROC curve for each gene to predict the best group of cells from all other cells.
a numeric matrix of normalized expression values, columns = samples, rows = genes.
a vector of group ids for each cell/sample.
Uses the ROCR package to calculate the AUC for each gene for the group with the highest average rank. Significant is calculated using a Wilcox rank-sum test.
A dataframe with a row for each gene and columns: AUC, Group (which label this gene had the highest average rank for), and pval (uncorrected p-value of prediction).
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