We clearly need more information about your experiment to help you
removing batch effects. Judging from your original email, it sounded
all of condition 1 was on batch 1 and all of condition 2 was run on
(ie this is perfect confounding). What exactly was run on Batch 1
(experiment 1) and what was run on Batch 2 (experiment 2)?
In your approach outlined below, you might still miss a lot, or have a
of false positives. But its hard to know without your experiment
Also depending on your experiment, if you're working in a well
system, like yeast or stem cells, biologists could probably give you a
lists genes that should change with a given treatment. you could see
variation across batches at these genes to see if SVA or ComBat is
Date: Mon, 12 Mar 2012 10:09:54 +0000
From: tefina <firstname.lastname@example.org>
Subject: Re: [BioC] batch effect confounded with condition
Content-Type: text/plain; charset="us-ascii"
Thanks for all your answers.
I think I will pursue the following strategy:
I will analyse each experiment separately. Contrasts within each
should be fine. (As batch 1 concerns only experiment 1 and batch 2
Any comparisons between experiments ( = comparisons between batches) I
do on the p value level. So I will only evaluate things like: do genes
up in experiment 1 also show up in experiment 2?
Doing this, I should be more or less on the safe side.
What do you think?
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