v.auc: v.auc

In DWLS: Gene Expression Deconvolution Using Dampened Weighted Least Squares

v.auc

Description

Uses the prediction() function in order to create standardized output from the data in order to perform an AUC calculation. The calculation results are rounded to the third decimal place. This function serves mainly to support the DWLS function.

Usage

v.auc(data.v, group.v)

Arguments

data.v	Data
group.v	Data subdivision

Value

Matrix of standardized output of AUC calculation

Examples

#dataSC
#url <- "https://github.com/sistia01/DWLS/raw/main/inst/extdata/dataSC.RData"
#dest <- "data/dataSC.RData"
#load(download.file(url, tempfile(data/dataSC.RData))
#load("dataSC.RData")
#SOLUTION
load(system.file("extdata", "dataSC.RData", package = "DWLS"))

#dataBulk
#url <- "https://github.com/sistia01/DWLS/raw/main/inst/extdata/dataBulk.RData"
#dest <- "data/dataBulk.RData"
#load(download.file(url, tempfile(dest)))
#load("data/dataBulk.RData")
load(system.file("extdata", "dataBulk.RData", package = "DWLS"))

#labels
#url <- "https://github.com/sistia01/DWLS/raw/main/inst/extdata/labels.RData"
#dest <- "data/labels.RData"
#download.file(url, dest)
#load("data/labels.RData")
load(system.file("extdata", "labels.RData", package = "DWLS"))

#data('trueLabels', package = "DWLS")
#url <- "https://github.com/sistia01/DWLS/raw/main/inst/extdata/trueLabels.RData"
#dest <- "data/trueLabels.RData"
#download.file(url, dest)
#load("data/trueLabels.RData")
load(system.file("extdata", "trueLabels.RData", package = "DWLS"))

pseudo.count = 0.1
data.used.log2   <- log2(dataSC+pseudo.count)
colnames(data.used.log2)<-make.unique(colnames(data.used.log2))
diff.cutoff=0.5
id = labels
for (i in unique(id)){
  cells.symbol.list2 = colnames(data.used.log2)[which(id==i)]
  cells.coord.list2 = match(cells.symbol.list2, colnames(data.used.log2))
  cells.symbol.list1 = colnames(data.used.log2)[which(id != i)]
  cells.coord.list1= match(cells.symbol.list1, colnames(data.used.log2))
  data.used.log2.ordered = cbind(data.used.log2[,cells.coord.list1],
                                         data.used.log2[,cells.coord.list2])
  group.v <- c(rep(0,length(cells.coord.list1)),
                               rep(1, length(cells.coord.list2)))
  #ouput
  log2.stat.result <- stat.log2(data.used.log2.ordered,
                                    group.v, pseudo.count)
m.auc=function(data.used.log2.ordered,group.v)
{AUC=apply(data.used.log2.ordered, 1, function(x) v.auc(x,group.v))
AUC[is.na(AUC)]=0.5
return(AUC)}

}

DWLS documentation built on May 24, 2022, 5:07 p.m.