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Hi,
I tired to use the training.data.
cellid = colnames(training.data)
cycles = sapply(cellid, function(x) { strsplit(x, "_")[[1]][1] })
timelab = sapply(cycles, function(x) {
if(x=="G1"){
y=1
}else if(x=="S") {
y=2
}else if(x=="G2M"){
y=3
}else{
y=0
}
y
})
ordIndex <- get_ordIndex(training.data, threadnum=4)
cor(ordIndex, timelab)
The results is 0.62.
Why the correlation is so small compared to the paper?
Thanks.
The text was updated successfully, but these errors were encountered:
Hi,
I tired to use the training.data.
cellid = colnames(training.data)
cycles = sapply(cellid, function(x) { strsplit(x, "_")[[1]][1] })
timelab = sapply(cycles, function(x) {
if(x=="G1"){
y=1
}else if(x=="S") {
y=2
}else if(x=="G2M"){
y=3
}else{
y=0
}
y
})
ordIndex <- get_ordIndex(training.data, threadnum=4)
cor(ordIndex, timelab)
The results is 0.62.
Why the correlation is so small compared to the paper?
Thanks.
The text was updated successfully, but these errors were encountered: