refineMIBC

This package implements a 120-gene template, that assigns subtype labels according to the multi-omics consensus ensemble of muscle-invasive bladder cancer (MIBC) using nearest template prediction. The consensus ensemble identifies 4 integrative consensus subtypes: basal-inflamed, basal-noninflamed, luminal-excluded, and luminal-desert. This package also deploys a 5-immune-gene classifier to refine each basal-like MIBC as either basal-inflamed or basal-noninflamed by random forest classifier if basal-like classification has been already identified by other approaches (e.g., CMS, PAM, oneNN, Lund, etc.).

Citation

For now, you can cite the following bioRxiv preprint

Installation

You may install this package with:

if (!require("devtools")) 
    install.packages("devtools")
devtools::install_github("xlucpu/refineMIBC")

Example

# load R package and internal data set
library(refineMIBC)
load(system.file("extdata", "demo.RData", package = "refineMIBC", mustWork = TRUE)) # load example data

# extract expression and TCGA subtype of MIBC
expr <- demo$MIBC.expr
subt <- demo$MIBC.subt

# refine MIBC into four subtypes
iCS  <- refineMIBC(expr       = expr, # expression data of MIBC
                   scaleFlag  = TRUE, # scale the data
                   centerFlag = TRUE) # center the data

head(iCS)
#                      prediction d.basal-inflamed d.basal-noninflamed d.luminal-desert d.luminal-excluded    p.value         FDR
# TCGA-HQ-A5NE-01A basal-inflamed        0.5413788           0.6479540        0.6007494          0.6973374 0.02797203 0.032200358
# TCGA-FD-A5BT-01A basal-inflamed        0.5420301           0.8216466        0.8498781          0.6313805 0.00100000 0.001455882
# TCGA-XF-AAMW-01A basal-inflamed        0.5475961           0.6043551        0.7397574          0.8120306 0.00100000 0.001455882
# TCGA-K4-A6FZ-01A basal-inflamed        0.5055447           0.6362818        0.5627713          0.8083026 0.00100000 0.001455882
# TCGA-BT-A42F-01A basal-inflamed        0.5338917           0.7166934        0.8419884          0.8426489 0.00100000 0.001455882
# TCGA-UY-A8OB-01A basal-inflamed        0.4858243           0.7400020        0.8302346          0.8539241 0.00100000 0.001455882

# refine basal-like MIBC into either basal-inflamed or basal-noninflamed
isbasal <- subt$TCGA == "Basal_squamous"
iBasal  <- refineBasal(expr    = expr,    # expression data of MIBC
                       isBasal = isbasal) # basal-like indicator
head(iBasal)
#              samID   prob       basal
# 1 TCGA-HQ-A5NE-01A 0.6500    inflamed
# 2 TCGA-FD-A5BT-01A 1.0000    inflamed
# 3 TCGA-XF-AAMW-01A 0.4545 noninflamed
# 4 TCGA-K4-A6FZ-01A 0.1965 noninflamed
# 5 TCGA-BT-A42F-01A 0.6350    inflamed
# 6 TCGA-UY-A8OB-01A 0.5295    inflamed