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This function takes as input a data.frame with genetic expression count data, and uses a bootstrapped leave-one-out cross validation procedure with logistic regression to allow for numeric and graphical comparison across any number of genetic signatures. It creates a boxplot of bootstrapped AUC values.


  signature.list = NULL, = NULL,
  num.boot = 100, = TRUE,
  name = "Signature Evaluation: Bootstrapped AUCs",
  fill.col = "white",
  outline.col = "black",
  abline.col = "red",
  rotateLabels = FALSE



a data.frame of gene expression count data. Required.


a numeric binary vector of the response variable. The vector should be the same number of rows as df. Required.


a list of signatures to run with their associated genes. This list should be in the same format as TBsignatures, included in the TBSignatureProfiler package. If signature.list = NULL, the default set of signatures TBsignatures list is used. For details, run ?TBsignatures.

A vector specifying the names of the signatures to be compared. This should be the same length as signature.list. If = NULL, the default set of signatures TBsignatures list is used.


an integer specifying the number of bootstrap iterations.

logical. If TRUE then a progress bar for the bootstrapping procedure will be displayed as output. The default is TRUE.


a character string giving a name for the outputted boxplot of bootstrapped AUCs. The default is "Signature Evaluation: Bootstrapped AUCs".


the color to be used to fill the boxplots. The default is "white".


the color to be used for the boxplot outlines. The default is "black".


the color to be used for the dotted line at AUC = 0.5 (the chance line). The default is "red".


logical. If TRUE, the x-axis labels will be rotated. The default is FALSE.


a boxplot comparing the bootstrapped AUCs of inputted signatures


inputTest <- matrix(rnorm(1000), 100, 20,
                    dimnames = list(paste0("gene",, 100)),
                                    paste0("sample",, 20))))
inputTest <-
targetVec <- sample(c(0,1), replace = TRUE, size = 20)
signature.list <- list(sig1 = c("gene1", "gene2", "gene3"),
                       sig2 = c("gene4", "gene5", "gene6")) <- c("sig1", "sig2")
num.boot <- 5
plotQuantitative(inputTest, targetVec.num = targetVec,
                 signature.list = signature.list,
                 num.boot = num.boot, rotateLabels = FALSE)
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