McpAUC: Clasification of area under ROC curve following McClish...

Description Usage Arguments Value Examples

Description

Calculate the area under the ROC curve following McClish methodologic from a dataset and a sample from that dataset.

Usage

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mcpAUC(
  dataset,
  low.value = NULL,
  up.value = NULL,
  plot = FALSE,
  selection = NULL,
  variable = NULL
)

Arguments

dataset

Dataframe of the complete information of the samples

low.value

lower false positive rate value that the function will use to calculate the pAUC

up.value

upper false positive rate value that the function will use to calculate the pAUC

plot

ROC plot

selection

vector that will only be used if the parameter "dataset" is a RangedSummarizedExperiment object. This parameter is used to select the variables that will be analysed

variable

in case that dataset is a SummarizedExperiment, indicate the Gold Standard

Value

RangedSummarizedExperiment object with the pAUC and the mcpAUC scores,and the TPR and FPR values for each ROC curve generated

Examples

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library(fission)
data("fission")
resultsMC <- mcpAUC(fission, low.value = 0, up.value = 0.25, plot = TRUE,
selection = c("SPNCRNA.1080","SPAC186.08c"), variable="strain")

juanpegarcia/ROCpAI documentation built on June 3, 2021, 5:42 a.m.