Dear r-sig-phylo community
I am writing to you in hopes of you giving me your inputs on a specific topic.
I noticed a rise of use of PCMs when it comes to gene expression data lately.
Many of these studies before fitting a specific model to their expression data
do several normalization steps. The common steps in order are to normalize for
sequencing depth and gene length, normalize in between replicates within
species and finally to normalize across species. For within species and across
species I have seen TMM normalization method being used (from edgeR package) or
batch effect removal (f.ex. Combat-seq function from sva package).
My concern is the final normalization step, namely to normalize continuous data
across species before model fitting. By doing so wouldn't one minimize the
phylogenetic signal present in the dataset, therefore affecting the best
fitting model?
Thank you in advance for your answer.
Best regards,
Ferenc Kagan
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