Hi all,

I have the following type of data:

• 5 batches (5 different data sets)
• 2 conditions (wt, mutant)
• 3 different tissues (data 1 and 2 represent tissue 1, data 3 and 4 represent tissue 2, data 5 represents tissue 3)

I would like to find DEGs in tissue 1 - mutant vs. other tissues (wt and mutant together), but I'm not sure how to specify the parameter for a tissue.

Here is what I would do for only batch and condition for the comparison mutant vs wt:

# preparing coldata 
    coldata=matrix(,22,3)
    coldata[,1]=colnames(countdata)
    colnames(coldata)=c("probe","condition","batch")
    coldata[1:4,3]=paste("data1")
    coldata[5:8,3]=paste("data2")
    coldata[9:12,3]=paste("data3")
    coldata[13:17,3]=paste("data4")
    coldata[18:22,3]=paste("data4")
    coldata[c(1:2, 5:6,9:10,13:15,18:20),2]=paste("mutant")
    coldata[c(3:4,7:8,11:12,16:17,21:22),2]=paste("wt")


# running DESeq2
    dds <- DESeqDataSetFromMatrix(countData = countdata, colData = coldata, design= ~ batch + condition)
    dds <- DESeq(dds)
    resultsNames(dds) # lists the coefficients
    res <- results(dds, name="condition_mutant_vs_wt")

Now I wonder how to include the tissue information and compare tissue 1 - mutant vs. other tissues (wt and mutant together).

For figuring out the right statistical design to answer questions of interest, I recommend working with a local statistician or someone familiar with linear models in R. Unfortunately, I have to limit my time on the support site to software related questions, and I can't field statistical consultation questions here.

You can make another column of Coldata whatever you want, and compare subsets of samples to subset of samples that way. But are you sure that you want to compare tissues to each other? Usually those differences are very large.