Question: Preprocessing for RNASeq data for CMSclassifier
gravatar for mas
16 months ago by
mas10 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 • 608 views
ADD COMMENTlink modified 14 months ago by Biostar ♦♦ 20 • written 16 months ago by mas10

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 14 months ago • written 14 months ago by ATpoint28k
Please log in to add an answer.


Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.3.0
Traffic: 1461 users visited in the last hour