Nothing
# GO over this again later to make sure it is done the right way ....
anota2seqDataSetFromMatrix <- function(
dataP,
dataT,
phenoVec,
batchVec = NULL,
dataType,
normalize = FALSE,
transformation = "TMM-log2",
filterZeroGenes = ifelse(dataType == "RNAseq" & normalize == TRUE, TRUE, FALSE),
varCutOff = NULL)
{
if(is.null(batchVec) == FALSE){
batchVec <- as.character(batchVec)
}
anota2seqCheckParameter(normalize,dataType,transformation,filterZeroGenes,varCutOff,inFunc="dataset")
anota2seqCheckInput(dataP,
dataT,
phenoVec,
batchVec,
NULL,
"BH",
inFunc="fromMatrix")
if(dataType == "RNAseq"){
preProcess <- anota2seqRNAseqPreProcessing(dataP=dataP,
dataT=dataT,
transformation =transformation,
filterZeroGenes=filterZeroGenes,
normalize=normalize)
dataT <- preProcess$dataT
dataP <- preProcess$dataP
}
# Check for genes that show low variance in the dataset ...
varCheck <- anota2seqFiltCheckVar(tmpdataP = dataP,
tmpdataT = dataT,
varCutOff = varCutOff,
phenoVec = phenoVec)
dataP <- varCheck$dataP
dataT <- varCheck$dataT
if(max(range(dataP)) > 100 | max(range(dataT)) > 100){
message()
stop("Input data range indicates a non continuous scale. \n
Make sure the input data is normalized and if coming from RNAsequencing transformed to a continuous scale.\n")
}
# initialize the Anota2seqDataSet class first so that checks on phenoVec and contrast get performed.
anota2seqClass <- new("Anota2seqDataSet",
dataP = dataP,
dataT = dataT,
phenoVec = as.character(phenoVec),
batchVec = batchVec,
contrasts = NULL,
qualityControl = NULL,
residOutlierTest = NULL,
translatedmRNA = NULL,
totalmRNA = NULL,
translation = NULL,
buffering = NULL,
selectedTranslatedmRNA = NULL,
selectedTotalmRNA = NULL,
selectedTranslation = NULL,
selectedBuffering = NULL,
mRNAAbundance = NULL,
deltaData = NULL,
regModes = FALSE)
message("All input checkpoints passed.\n")
return(anota2seqClass)
}
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