PDSclassifier R package provides a pathway-based molecular classification system for colorectal cancer (CRC), which can be applied to gene expression profiles to stratify into three PDS (Pathway-Derived Subtype): PDS1, PDS2 and PDS3, with distinct molecular biology.
You can install the development version of PDSclassifier like so:
if(!requireNamespace("devtools", quietly = TRUE))
install.packages("devtools")
devtools::install_github('sidmall/PDSclassifier')An example where using the test dataset from the R package, PDS classification can be made with PDSpredict() function.
library(PDSclassifier)
pds_calls <- PDSpredict(testData, species = 'human', threshold = 0.6)PDSclassifier can be applied to both human and mouse transcriptomic data with parameter:
species = c("human", "mouse").
The default prediction probability threshold = 0.6 has been set. It can be altered anywhere between 0 (less stringent) to 1 (very stringent). However, recommendation is be stay between 0.5-0.7 to retain enough samples without losing underlying biology that defines PDS.
Additionally, calculateSMI() function allows users to get a transcriptomic measure along the stem-to-differentiation scale.
smi_data <- calculateSMI(as.matrix(testdata[,-1]), datatype = "bulk", species = "human")The outcome provides single sample gene set enrichment analysis (ssGSEA) score for MYC targets and PRC targets, and from these Stem Maturation Index (SMI) is calculate (provided unscaled and scaled (-1 to 1)).