Hi,
I'm using DESeq2 and I have a continuous covariate in the model. Also, instead of size factors, I have the Normalization Factor Matrix (NF) to account for GC content bias. I have a few questions:
(1) Is this the correct way to access the normalized counts, now that I'm using the NF matrix?
counts(dds,normalized=T)
(2) I'm not sure what the log2FoldChange for this covariate represents:
(2.1) If the covariate were not continuous and I could represent it as a factor, would the log2Foldchange be equal to log2 of ratio of normalized means, for the last two factor levels?
(2.2) If so, then how would this translate to the continuous case? I know that it is per unit of change of the continuous covariate. But for some genes, I'm getting high log2FoldChange values, but when I plot the "read counts" as a function of the continuous covariate, I'm not observing a high change in count values as the continuous covariate increases. Why is that the case?
(2.3) Will I get a better interpretation of the log2FoldChange value if I plot the "normalized counts" against the continuous covariate (considering that I'm using the NF matrix)?
I'd deeply appreciate any help or comment.
Thanks,
Golsheed
I'm using DESeq2 and I have a continuous covariate in the model. Also, instead of size factors, I have the Normalization Factor Matrix (NF) to account for GC content bias. I have a few questions:
(1) Is this the correct way to access the normalized counts, now that I'm using the NF matrix?
counts(dds,normalized=T)
(2) I'm not sure what the log2FoldChange for this covariate represents:
(2.1) If the covariate were not continuous and I could represent it as a factor, would the log2Foldchange be equal to log2 of ratio of normalized means, for the last two factor levels?
(2.2) If so, then how would this translate to the continuous case? I know that it is per unit of change of the continuous covariate. But for some genes, I'm getting high log2FoldChange values, but when I plot the "read counts" as a function of the continuous covariate, I'm not observing a high change in count values as the continuous covariate increases. Why is that the case?
(2.3) Will I get a better interpretation of the log2FoldChange value if I plot the "normalized counts" against the continuous covariate (considering that I'm using the NF matrix)?
I'd deeply appreciate any help or comment.
Thanks,
Golsheed
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