Hello! I'm quite new to DESeq. I want to compare two treatments with only one replicate each. I heard the DESeq package can handle this sort of data. My data looks like this:
data <- read.csv("C:/data.csv", header=T, sep=";", row.names=1) str(data) 'data.frame': 5538 obs. of 2 variables: $ BC_SN: int 2595 5794 1013 6715 368 74 185 2006 545 16 ... $ PA_SN: int 2994 7947 1135 7728 362 55 157 1553 429 23 ... metadata <- data.frame(row.names = colnames(data), condition = c("treated", "untreated")) > metadata condition BC_SN treated PA_SN untreated
I then generate a countdataset by using:
cds <- newCountDataSet( countData = data, conditions = metadata )
CountDataSet (storageMode: environment) assayData: 5538 features, 2 samples element names: counts protocolData: none phenoData sampleNames: BC_SN PA_SN varLabels: sizeFactor condition enter code here featureData featureNames: PA0001 PA0002 ... PA5570 (5538 total) fvarLabels: disp_blind fvarMetadata: labelDescription experimentData: use 'experimentData(object)' Annotation:
My further script is:
cds <- estimateSizeFactors(cds) cds <-estimateDispersions(cds,method="blind",sharingMode="fit-only",fitType="local") res <- nbinomTest(cds,"treated","untreated")
The nbinomTest function gives me this error:
Error in if (dispTable(cds)[condA] == "blind" || dispTable(cds)[condB] == : missing value where TRUE/FALSE needed
I don't understand this error or what I can do to make the nbinomTest function work.
my dispTable looks like this:
> dispTable(cds) _all "blind"
Can somebody help me please?
BTW, I know only one replicate doesn't tell me much about the biological effects. I'm working on two more already but in the meantime I would like to look into some of my data already.