plotQuantitative {TBSignatureProfiler} | R Documentation |
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.
plotQuantitative( df.input, targetVec.num, signature.list = NULL, signature.name.vec = NULL, num.boot = 100, pb.show = TRUE, name = "Signature Evaluation: Bootstrapped AUCs", fill.col = "white", outline.col = "black", abline.col = "red", rotateLabels = FALSE )
df.input |
a |
targetVec.num |
a numeric binary vector of the response variable.
The vector should be the same number of rows as |
signature.list |
a |
signature.name.vec |
A vector specifying the names of the signatures
to be compared. This should be the same length as |
num.boot |
an integer specifying the number of bootstrap iterations. |
pb.show |
logical. If |
name |
a character string giving a name for the outputted boxplot of
bootstrapped AUCs. The default is |
fill.col |
the color to be used to fill the boxplots.
The default is |
outline.col |
the color to be used for the boxplot outlines.
The default is |
abline.col |
the color to be used for the dotted line at AUC = 0.5
(the chance line). The default is |
rotateLabels |
logical. If |
a boxplot comparing the bootstrapped AUCs of inputted signatures
inputTest <- matrix(rnorm(1000), 100, 20, dimnames = list(paste0("gene", seq.int(1, 100)), paste0("sample", seq.int(1, 20)))) inputTest <- as.data.frame(inputTest) targetVec <- sample(c(0,1), replace = TRUE, size = 20) signature.list <- list(sig1 = c("gene1", "gene2", "gene3"), sig2 = c("gene4", "gene5", "gene6")) signature.name.vec <- c("sig1", "sig2") num.boot <- 5 plotQuantitative(inputTest, targetVec.num = targetVec, signature.list = signature.list, signature.name.vec = signature.name.vec, num.boot = num.boot, rotateLabels = FALSE)