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Comment: DESeq2, results(dds, name = <reference>) interpretation results
by
Rockbar
• 0
When I apply the model.matrix approach for getting the contrasts, the code > mod_mat <- model.matrix(design(dds), colData(dds)) > CondA.t…
Comment: DESeq2, results(dds, name = <reference>) interpretation results
by
Rockbar
• 0
Yes, I agree, the correct contrast setting is quite challenging. The vignette says >contrast: a list of 2 character vectors: the names of…
Comment: Does countsFromAbundance="lengthScaledTPM" produce un-normalized counts?
by
Michael Love
40k
Advantage and disadvantage depends on the aim, what you plan to do with them (testing, plots, etc.). lengthScaledTPM puts back *in* the ge…
Comment: DESeq2, results(dds, name = <reference>) interpretation results
by
James W. MacDonald
63k
No, putting -1 in the design matrix is a cell means model, which is the opposite. If you used `~ Cond + Cond:Time`, you would specify a fac…
Comment: Does countsFromAbundance="lengthScaledTPM" produce un-normalized counts?
by
Christian
• 0
Thank you for the response and apologies for my late reply. I think I´m starting getting the concept now. The hints with the cqn is quite …
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Answer: Does countsFromAbundance="lengthScaledTPM" produce un-normalized counts?
Answer: Does countsFromAbundance="lengthScaledTPM" produce un-normalized counts?
Answer: Does countsFromAbundance="lengthScaledTPM" produce un-normalized counts?
Answer: Remove duplicates of colData in TreeSummarizedExperiment
Answer: Remove duplicates of colData in TreeSummarizedExperiment
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