TIerror: Type I error
In emodoro/dEMO: Differential Expression and confidencial estimation for FC

Description Usage Arguments Value Author(s) Examples

TIerror is a functions which allow plotting the type I error commited by several hypothesis testing methods, shuch a several Differential Expression analysis.

1	TIerror(dataRoc, resample = 100, main)

`dataRoc`	a data.frame where each column stores p values from each of the hypothesis test methods which are wanted to compare. The last column store the information related to real differential expression, where "0" means no differential expression and "1" means differential expression.
`resample`	The number of resamplings of genes from data set in order to construct a boxplot from several samples from just one data set. Default value is 100.
`main`	the title of the plot

a box plot with the Type I error for every and each one of hypothesis test methods

Enrique Perez_Riesgo

library(compcodeR)
library(edgeR)
set.seed(123456987)
datasCI<-generateSyntheticData(dataset = EMOresults, n.vars = 15000,samples.per.cond = 6, n.diffexp = 1500,repl.id = 1, seqdepth = 1e7,fraction.upregulated = 0.5,between.group.diffdisp = FALSE,filter.threshold.total = 1,filter.threshold.mediancpm = 0,fraction.non.overdispersed = 0)
expressiondata<-datasCI@count.matrix
TMMfac<-calcNormFactors.default(expressiondata,method = "TMM")
exprT<-t(t(expressiondata)*TMMfac)
conditions<-(datasCI@sample.annotations$condition-1)
testEMOTMM<-EMObuODlmTest(expr=exprT, condition = conditions,original = exprT,originalm=exprT)
edgeR.dgelist = DGEList(counts = expr, group = factor(conditions))
edgeR.dgelist = calcNormFactors(edgeR.dgelist, method = "TMM")
edgeR.dgelist = estimateCommonDisp(edgeR.dgelist)
edgeR.dgelist = estimateTagwiseDisp(edgeR.dgelist, trend = "movingave")
edgeR.test = exactTest(edgeR.dgelist)
edgeR.pvalues = edgeR.test$table$PValue
edgeR.adjpvalues = p.adjust(edgeR.pvalues, method = "BH")
testedgeRTMM<-data.frame(FC=edgeR.test$table$logFC, PVALUE=edgeR.test$table$PValue, ADJ.PVAL=edgeR.adjpvalues)
dataRoc<-data.frame(EMO=testEMOTMM$ADJ.PVAL,edgeR=testedgeRTMM$ADJ.PVAL, DE=expr3@variable.annotations$differential.expression)
TIerror(dataRoc = dataRoc, resample=100, main="Type I Error")