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How can I specify DEseq2 to only perform comparisons on which I am interested with ?

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  • How can I specify DEseq2 to only perform comparisons on which I am interested with ?

    Hello all,

    I am currently performing a large RNA-seq analysis from mice PBMCs. The dataset contains around 6,000 transcriptomic profiles and I would like to use DESeq2 to identify the sets of differentially expressed genes in the different conditions. In total, I have 100 biological stimulations, and for each stimulation I have 30 control samples and 30 samples treated with a molecule of interests (so is have: (30 controls+30 treated) * 100 stimulations = 6,000 samples).

    I want to identify, for each stimulation, the sets of differentially expressed genes between control samples and treated samples. I do not want to compare samples from the different stimulations. In total, I would like to have thus 100 lists of differentially expressed genes.

    I have started to use deseq2 to identify these lists but deseq2 is spending lot of time to perform comparisons on which I am not interested with (comparisons between the biological stimulations).

    For now, I have a table sampleTable which looks like that:

    I am using DEseq2 using the following command:

    DESeqDataSetFromHTSeqCount(sampleTable = sampleTable, directory = directory, design= ~ condition)
    Could you please help me with that? How can I specify to deseq2 to not perform the comparisons between the biological stimulations, but rather between control and treated sample within each stimulation ?

    Thank you and best,
    Attached Files

  • #2
    You may want to just split the data up into per-stimulation chunks. Otherwise the modeling in DESeq2 will use all samples and all stimulations to establish dispersions. If the separate stimulations are meant to be experimentally separate then you should not put all of the into the same model. So you'll run 'DESeqDataSetFromHTSeqCount' 100 times each with a subset of your data corresponding to a single stimulation.
    /* Shawn Driscoll, Gene Expression Laboratory, Pfaff
    Salk Institute for Biological Studies, La Jolla, CA, USA */