#### README #####


This R script can be run in any linux machine with R installed with openxlsx and argparser packages.

The software has been tested on a Ubuntu 20.04, R version 4.2.1, openxlsx R package version 4.2.5 and argparser R package version 0.7.1


To run the script, type this in the linux terminal (it should take no more than a few seconds):

Rscript Vigex_calculation.R --expression expression_input_vigex.xlsx


Be aware of use log2 expression values. The script will take care of centering the expression values.
Be also aware of the spelling (the software is case-sensitive) of the genes, the genes included in the VIGex Score calculation must be spelled exactly as follows: "CTLA4", "IL7R", "GZMA", "PRF1", "IFNg", "PDCD1", "FOXP3", "CXCL9", "CXCL10", "CXCL11", "GZMB", "CD274"


The output file will be an excel file with 3 columns:
- samples: name of the samples analysed
- vigex_score: VIGex Score
- vigex_cluster: VIGex Cluster


######################################################################################################################
### Caution: the used cutoffs have been validated in the training dataset presented in this paper.                ####
### If you are using vigex in other samples/techniques, you'll probably have to correct for batch effects.        ####      
### Moreover, this is a score/sample grouping developed in a pan-cancer cohort, if your cohort is tumor-specific, ####
### you may have to apply further corrections or other techniques to obtain the Hot/iCold/Cold categories.        ####      
######################################################################################################################



If you need to normalize nanostring, you can take a look to nanostring_normalization.R R script.