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MT ▴ 10@mt-12730
Last seen 3.3 years ago
Hello, I am a novice and I am interested in comparing two kind of cells coming from different RNA sequencing experiments published. The design would be something like the following:
sample cell batch 1 type1 1 2 type1 1 3 type1 1 4 type1 2 5 type1 2 6 type2 3 7 type2 3 8 type2 3 9 type2 4 10 type2 4
Now, naturally I cannot model del batch effect with ~ batch + cell because the batch is nested in the condition "cell". But the question remains, what is the best way to compare type 1 and type 2 taking into consideration and mitigating possibile batch effects?
Thanks for your help. Best, Marco
Perhaps you can try surrogate variable analysis?
Surrogate variable analysis isn't magic, and won't fix confounding.
Think of it this way. If you had a study where you treated a group of patients with a drug and had a group of patients who were controls, but at the same time all of the treated patients were smokers and the controls were not, how would you ever know if any differences were due to the treatment or the smoking?
SVA is just a way to adjust out unobserved factors, but it won't help with completely confounded variables. There is no magic way to fix that.