Create a boxplot using logistic regression and bootstrap LOOCV to evaluate signatures.
Source:R/evaluate.R
plotQuantitative.Rd
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.
Usage
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
)
Arguments
- df.input
a
data.frame
of gene expression count data. Required.- targetVec.num
a numeric binary vector of the response variable. The vector should be the same number of rows as
df
. Required.- signature.list
a
list
of signatures to run with their associated genes. This list should be in the same format asTBsignatures
, included in the TBSignatureProfiler package. Ifsignature.list = NULL
, the default set of signaturesTBsignatures
list is used. For details, run?TBsignatures
.- signature.name.vec
A vector specifying the names of the signatures to be compared. This should be the same length as
signature.list
. Ifsignature.name.vec = NULL
, the default set of signaturesTBsignatures
list is used.- num.boot
an integer specifying the number of bootstrap iterations.
- pb.show
logical. If
TRUE
then a progress bar for the bootstrapping procedure will be displayed as output. The default isTRUE
.- name
a character string giving a name for the outputted boxplot of bootstrapped AUCs. The default is
"Signature Evaluation: Bootstrapped AUCs"
.- fill.col
the color to be used to fill the boxplots. The default is
"white"
.- outline.col
the color to be used for the boxplot outlines. The default is
"black"
.- abline.col
the color to be used for the dotted line at AUC = 0.5 (the chance line). The default is
"red"
.- rotateLabels
logical. If
TRUE
, the x-axis labels will be rotated. The default isFALSE
.
Examples
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)
#>
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