Thanks for the answer.
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Should I do normalization to gene/features or samples?
Hi,
I am learning pre-processing metabolomic LC/MS data. For example, I have a data, df, and it has features in rows, and samples in columns. If I want to do z-score normalization, should I do to each sample group or feature?
I am thinking on each features, but I am not sure. For the code in R, I use scale(),
apply(df, 1, function(x) scale(x, center = TRUE, scale= TRUE))
Should I do similar to RNAseq data as well, either to gene or sample?
Thank you.
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