I want to normalize metabolomics 'counts' data by Variance Stabilizing Transformation. In the meantime I already did that by VST function of using DESeq package and this improve in my opinion the clustering between replicates on a PCA plot which make sense for me. However I just wonder if I need actually use some modification on the function to avoid include library size normalization and what is different regarding the old VSN function of Limma package. Maybe I should be use that instead the implemented VST on DESeq? I mean; Is DESEq using a wrapper of VSN Limma for permom the VST or doing something else to normalize by library size? Any comment regarding my approach will be appreciated guys,
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panconchoclo •
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Is there any reason why you decided to use the variance stabilising transformation? From my experience, most log2 transform the peak areas (after QC), followed by a further Z-scale transformation. Admittedly, this is not ideal. Metabolomics suffers from a lack of reproducibility, and exhibits high variability, as you are probably aware.
I would post this over at BioC to get a response from Mike Love (the DESeq2 maintainer/developer). Don't forget to post a couple of plots to show how your data are distributed and give some background information on the nature of these data, e.g. if they follow a certain distribution and how replicates compare to each other.
Hi guys thank you for your reply.
Kevin I decided by VST because there are Heteroscedasticity. The behaviour of Means vs SD after and before VST transformation in my data is showed.
In the plot 1 you will see that there are some metabolites with a lot of variance. After VST the differences are slower (see scales of Y axis)
before VST normalization(raw data):
after VST:
If I do the PCA of raw data my replicates are not all of them together. If I do VST before PCA the behavioir in this sense is better. I mean my replicates are closer between them.
I would go with the suggestion of ATpoint and ask this on the Bioconductor forum. Michael Love will provide an answer or comment.
Thank you Kevin I will do that. To avoid repeat exactly the same question there I will dig more in detail on these packages.