Correcting partially penetrant batch effect
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swbarnes2 ▴ 710
@swbarnes2-14086
Last seen 9 hours ago
San Diego

I have a control set of samples, and 3 viruses, each exposed to two treatments. 5 replicates of each. In two viruses, in both treatments, the first two replicates are left shifted in the PC1 values compared to the other replicates, example:

  • virus1_treatment1_Rep1 -26.21084691
  • virus1_treatment1_Rep2 -23.81517717
  • virus1_treatment1_Rep3 -13.52695811
  • virus1_treatment1_Rep4 -10.74887635
  • virus1_treatment1_Rep5 -10.11061144

but in the controls, and the third virus, all 5 replicates look the same. I have results using a design of ~ virus_treatments + replicate, but I was wondering if that was right when the replicate effect is so different between the different viruses.

Is there a better way to deal with this?

DESeq2 • 87 views
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@mikelove
Last seen 13 hours ago
United States

Not really, the whole point is that the replicates account for within group variability. You can always access quality of a sample through independent measures, and then exclude on objective criterion.

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