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CMScaller: microenvironment-independent colorectal cancer consensus molecular subtyping

The CMScaller package provides Consensus Molecular Subtype (CMS) classification of colorectal cancer pre-clinical models [Guinney 2015; Eide 2017; Sveen 2017]. A small ensembl of functions for evaluating and visualizing results is also included. The core algorithm is Nearest Template Prediction (NTP) algorithm proposed by Yujin Hoshida [Hoshida 2010]. See accompagnying vignette for further details.

Install

From R/RStudio uncomment as required and run the following code

### dependencies: run if not already installed
### limma has lof of dependencies - takes time
# source("https://bioconductor.org/biocLite.R")
# biocLite(c("Biobase", "limma"))
# install.packages("devtools")

### install: latest version
devtools::install_github("Lothelab/CMScaller")

Quick start

library(Biobase)
library(CMScaller)
par(mfrow=c(1,2))

### CMS prediction of TCGA primary colorectal cancers
res <- CMScaller(crcTCGAsubset, RNAseq=TRUE, doPlot=TRUE)
head(res)

### Camera Gene Set Analysis with CMS informative gene sets
cam <- CMSgsa(emat=crcTCGAsubset, class=res$prediction, RNAseq=TRUE)
head(cam$CMS4)

### limma differential gene expression analysis and visualization
deg <- subDEG(emat=crcTCGAsubset, class=res$prediction, doVoom=TRUE)
subVolcano(deg, geneID="symbol")

Design

Package builds on Bioconductor to facilitate integration with existing workflows [Huber 2015] and was developed in RStudio following guidelines in R packages [Wickham 2015].

References

Eide PW, Bruun J, Lothe RA, Sveen A. CMScaller: an R package for consensus molecular subtyping of colorectal cancer pre-clinical models. Sci Rep. 2017. https://www.nature.com/articles/s41598-017-16747-x

Guinney J, Dienstmann R, Wang X, de Reynies A, Schlicker A, Soneson C, et al. The consensus molecular subtypes of colorectal cancer. Nat Med. 2015;21:1350-6. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4636487/

Hoshida, Y. Nearest Template Prediction: A Single-Sample-Based Flexible Class Prediction with Confidence Assessment. PLoS ONE 2010;5, e15543. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2990751/

Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, et al. Orchestrating high-throughput genomic analysis with Bioconductor. Nat Meth. 2015;12:115–21.

R Core Team. R: A Language and Environment for Statistical Computing [Internet]. Vienna, Austria: R Foundation for Statistical Computing; 2013. http://www.R-project.org/

Sveen A, Bruun J, Eide PW, Eilertsen IA, Ramirez L, Murumägi A, et al. Colorectal cancer Consensus Molecular Subtypes translated to preclinical models uncover potentially targetable cancer-cell dependencies. Clin Cancer Res. 2017. http://clincancerres.aacrjournals.org/content/early/2017/12/14/1078-0432.CCR-17-1234

Wickham, H. R Packages: Organize, Test, Document, and Share Your Code. 1st ed. O’Reilly Media. 2015.

Wickham, H. Chang, W. devtools: Tools to Make Developing R Packages Easier. R package version 1.13.0. 2017.

Wickham, H., Danenberg, P., Eugster, M. roxygen2: In-Line Documentation for R. R package version 6.0.1. 2017.