classifyCMS: classifyCMS

In Sage-Bionetworks/CMSclassifier: prediction of the Consensus Molecular Subtype (CMS) of colorectal carcinomas based on log2_scaled Gene Expression Profiles (GEP)

Description

predict the Consensus Molecular Subtype (CMS) of colorectal cancer samples, based on log2_scaled GEP

Usage

classifyCMS(Exp,method=c("RF","SSP"))

Arguments

Exp	a dataframe with log2_scaled Gene Expression Profiles (GEP) data values, samples in columns, genes in rows, rownames corresponding to Entrez IDs
method	a character vector, accepted values are: RF = random forest predictor (here data will be automatically row-centered) ; SSP = single sample predictor , based on correlation to centroids (the data won't be row-centered)

Value

a dataframe, samples in rows, columns : output of the predictor(s)

Note

This is a contribution from the Tumor Identity Cards (CIT) program founded by the 'Ligue Nationale Contre le Cancer' (France): http://cit.ligue-cancer.net. For any question please contact [e-mail]

Author(s)

Aurelien de Reynies

Sage-Bionetworks/CMSclassifier documentation built on May 9, 2019, 12:10 p.m.