Scripts_Details.rtf

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The Scripts are in the following order: \
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1: QCfilter.R. This script was used in order to perform a preprocessing of gene expression microarray data downloaded from public repositories and \
prior to any normalization.\
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2: Mutual_Exclusivity_Script.R. This script was used in order to run the mutual exclusivity analysis and in particular to calculate the \
significance of the enrichment of the mutually exclusive mutated genes in the CM-GRNs with respect to randomly generated networks. The script \
takes in input two files: "CM_Nets_TCGA_mutational_data_1.txt" that contains three columns: the list of the CM-GRNs in the first column, the number of \
mutually exclusive mutated genes in the network in the second column and the total set of patients that were considered (TCGA mutational data) in the third column. \
The second input file is called: "RANDOM_Nets_TCGA_mutational_data_1.txt". This file contains the same type of information of the previous one \
but it refers to randomly generated networks. The "*_1*" in both file names refers to the single gene mutual exclusivity. The mutual exclusivity \
was also investigated between groups of genes (e.g. couples of mutually exclusive mutated genes) although in the manuscript only single genes \
were considered. \
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3: Parallel_Aracne script. This script was used to speed up and parallelise the ARACNE calculations on the computer cluster because of the high number of HUBS (1,516 genes against the whole transcriptome)  to be tested in the reverse engineering analysis performed on: breast cancer and Glioblastoma, Lung  (LUSC, LUAD) and Ovarian Cancer \
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4: Concordance analysis.R. This script was used to calculate the Activation Score (AS) of the networks relative to the expression profile of breast cancer patients form the Metabric cohort. In particular, the script transforms the original continuous data matrix in a discrete 0-1 indexed matrix in order to calculate the AS i.e. the number of genes of each network having the same or the opposite expression pattern with respect to the transcriptional profile of the hub gene. The hub-gene neighbourhood of each GRNs, was matched with the genes of the Metabric cohort after the expression matrix transformation.\
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