Hi everyone,
I have a RNA-seq expression count matrix of 2 contrast conditions (~10 biological samples per condition), but these conditions are affected by (severe) batch effect from different sequencing experiments. I looked up for some batch-effect removal tools, but they could only fix batch-effect for samples of same condition group (different conditions may contain large true biological variations that account for most of batch-effect difference).
I plan to choose a group of housekeeping genes to adjust for this group difference, but I am still confusing about practical steps to do that. Could you please give me some suggestions? Here are some thoughts I am still questioning:
Thank you very much.
Yeah, I also thought so.
However, you know that it isn't practical to write in a research proposal something for example: "we need to collect 100 brain tissues from these patients with disease and also collect dozen of fresh brain pieces from normal people just to perform RNAseq experiments at the same condition"
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What separates these "batch groups"? Different library preps, sequencing machine?
Yes, because I obtained them from different public databases, so 2 experiment protocols were totally different (however both data are Hiseq Illumina reads)
Then I see little chance of using them in the same analysis, especially because you have absolutely no way of validating the results by an independent experimental approach.