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Comment: Numerical differences in DESeq2 output depending on different design matrix cons
by
Ken C
•
0
Well, if I look at genes with baseMean>50, then the relative absolute difference in log2FoldChange (say over the absolute log2FoldChange of…
Comment: all variables in design formula must be columns in colData (Deseq2) error
by
Galina
•
0
Thank you for advice,
you mean I need to add:
countdata_rat <- data.frame(condition = as.factor(METADATA_RAT$treatment))
and total:
dds_…
Answer: all variables in design formula must be columns in colData (Deseq2) error
by
ATpoint
★
4.1k
Your code is poorly readable. Suggest you select and then highlight with markdown using the `10101` button.
Generally, colData(dds) must…
Answer: Subsetting RNAseq data | voomaByGroup()
by
Gordon Smyth
50k
Judging from your MDS plot, cell types 1 and 2 look radically different, so it would make perfect sense to analyse them separately. There's…
Answer: Numerical differences in DESeq2 output depending on different design matrix cons
by
Michael Love
42k
Yes there can be small numerical differences in the estimated quantities because of how the algorithms decide to stop iterating.
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