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The SF in the output file (test_SF.txt) is scale factor and DGEList function in edgeR needs normalization factors. So I think the
norm.factors should be 1/SF.
It is always correct to use SF in this way dge <- DGEList(counts = counts, group = GROUP, norm.factors = SF)
When 100% complete loss is true, please note that there is NO accurate way to calculate a SF because there is no true signal in these samples. The proposed transformation is to assign an arbitrary value 1 to this sample group and scale down the other group to make a pseudo- scaling factors. It is ONLY suitable for a naïve design having only two groups. In a design like controls (n=3, real SFs= 2, 2, 3), vs ko(n=3, real SFs=NA, NA,NA) . The pseudo-SFs will be 0.5,0.5,0.3 (controls) and 1,1,1 (ko) so that you can see a global decrease in ko group.
Hello,
The SF in the output file (test_SF.txt) is scale factor and DGEList function in edgeR needs normalization factors. So I think the
norm.factors should be 1/SF.
should be:
And in the part: What happens if 100% complete loss is expected? You just used 1/SF. This is a little confusing.
Would you please clarify this issue?
Thanks
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