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built vignette using knitr
knitr
vignettes
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bioccheck
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7.5 years ago
kmezhoud
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Comment: Phenotype effect - building a contrast matrix - grouping vs interaction
by
Gordon Smyth
48k
I am telling you that `LS_B.vs.NL_B` is completely uninteresting. You need instead to examine `LS_Y.vs.NL_Y` and `LS_N.vs.NL_N` separately.
Answer: Batch correction and repeated measures
by
Gordon Smyth
48k
You should just do a standard limma analysis as recommended in the previous posts. ``` design <- model.matrix(~0 + Sample.Type + batch) i <…
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…
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Comment: Phenotype effect - building a contrast matrix - grouping vs interaction
Answer: Batch correction and repeated measures
Answer: Batch correction and repeated measures
Answer: Batch correction and repeated measures
Answer: Does countsFromAbundance="lengthScaledTPM" produce un-normalized counts?
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