Question: Preprocessing for RNASeq data for CMSclassifier
gravatar for mas
6 months ago by
mas0 wrote:

I am interested in comparing the Consensus Molecular Subtypes (CMS) labels from the random forest and single sample predictor methods from the package CMSclassifier. I have RNASeq data as raw counts as outputed by HTSeq. The CMSclassfier::classifyCMS.RF requires as input "log2_scaled Gene Expression Profiles (GEP) data values". Is it sufficient to log2 the raw counts from HTSeq or would it be more appropriate to also quantile-normalize the log2 values as in the CMScaller package? Or is there a more suitable normalization that you would recommend in these settings?


normalization rna-seq R • 278 views
ADD COMMENTlink modified 5 months ago by Biostar ♦♦ 20 • written 6 months ago by mas0

I would go for either rlog or vst transformation, as recommended for downstream analysis in the DESeq2 manual for classification/clustering and machine learning applications.

ADD REPLYlink modified 5 months ago • written 5 months ago by ATpoint15k
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