The BCR model of Prostate Cancer

Install

install.packages("devtools")
library(devtools)
install_github("daizao/PCaMLmodel")

Sample 1

#test data

# fat_stemness_BCR_Score model:
library(PCaMLmodel)
library(survival)
scores <- fat_stemness_BCR_Score(test_input_data)
scores

Sample 2

#if your data was input as data.frame

library(PCaMLmodel)
library(data.table)
library(tidyverse)
library(survival)

#such as your input file was named test.txt
#the format like 
#sampleid gene1 gene2 gene3...
#TCGA-2A-A8W3-01	509.250122221517	371.812665359136	192.037124283762
#TCGA-CH-5788-01	188.721606594081	900.654359416522	344.648267600287

data <- fread("test.txt",header = T,sep = '\t') %>%
      column_to_rownames(var = "sampleid")

# fat_stemness_BCR_Score model:
result <- fat_stemness_BCR_Score(as.matrix(data)) %>%
	as.data.frame()

colnames(result) <- "score"
result <- rownames_to_column(result,var = "sampleid")
result

Website

PCaMLmodel

Citation

If you find the model useful for your research, please cite the relevant papers

Machine-Learning–Based Prediction of Biochemical Recurrence in Prostate Cancer Integrating Fatty-Acid Metabolism and Stemness