Im taking stage specific data so for one set im taking from one publication and other set from a different publication now the question comes about the batch since there might be many factors contributing to noise which might not contribute to the true biological variability so how do i remove the batch effect so i came across combat ,RUV ,sva, but there is also in deseq2 to define batch to resolve the batch effect .
so I have 4 sample from HSC and 2 sample from granulocyte which is from a different publication so im trying to define it in my design but im getting error there been similar issue i read but im not able to resolve ..
countdata <- read.table('HSC_Gran.txt', header=TRUE, row.names=1)
countdata <- countdata[ ,6:ncol(countdata)]
colnames(countdata) <- colnames(countdata)
countdata <- countdata[rowSums(countdata)>10,]
countdata <- as.matrix(countdata)
condition <- factor(c(rep("Control", 4),rep("Test", 2)),levels=c("Control", "Test"))
batch <- factor(c(rep("A", 4),rep("B", 2)),levels=c("A", "B"))
(coldata <- data.frame(row.names=colnames(countdata), condition,batch))
dds <- DESeqDataSetFromMatrix(countData=countdata, colData=coldata, design=~condition:batch)
Error in checkFullRank(modelMatrix) : the model matrix is not full
rank, so the model cannot be fit as specified. One or more variables
or interaction terms in the design formula are linear combinations
of the others and must be removed.
Please read the vignette section 'Model matrix not full rank':
I'm doing something incorrect in my design ,any suggestion or help would be highly appreciated