This package contains the pipeline and tools developed for the study entitled "Immune Cell Associations with Cancer Risk". This pipeline was developed and is maintained by Luis Palomero and Roderic Espin (MA Pujana’s lab, Catalan Institute of Oncology, IDIBELL).
The pipeline includes the R package ConsensusTME (Jiménez-Sánchez et al., 2019; https://github.com/cansysbio/ConsensusTME), ssGSEA in Gene Set Variation Analysis (GSVA) (Hänzelmann et al., 2013; 10.18129/B9.bioc.GSVA), R/qtl2 (Broman et al., 2019; https://github.com/rqtl/qtl2), and bestNormalize (https://github.com/petersonR/bestNormalize).
To install it use the R package devtools and its function install_github. Open an R session and enter the following commands:
install.packages(c("devtools","curl")) ##Installs devtools
library(devtools)
install_github("pujana-lab/systematicBNR",ref="master")
Before running the regression analysis, three steps should be completed: 1) delete cases with empty data and covariables without variability; 2) apply bestNormalize regression to output variable; 3) apply Stepwise AIC pipeline to delete covariables non-informative. The main function output (systematic_regression) returns the results as 1-row data.frame object, ideally defined to run in a loop.