Table 7.

Important key metrics of datasets and corresponding analyses performed for each dataset. The two studies used, TCGA Legacy and CPTAC, are located in the first column [39,40,50,51]. The “datasets” column represents the type of omic dataset used from the corresponding study in column one, with key metrics identified. The “analyses” column represents the type of analysis performed on each specified dataset. “RSEM” = RNA-sequencing by expectation-maximisation. “UQ” = upper quantile normalisation. “TMT” = tandem mass tag.

Study	Datasets	Analyses
2016 TCGA Colorectal Adenocarcinoma, GDAC Firehose Legacy	1. Genomic from RNA Sequencing 20,532 genes Cohort of 329 patients 2. Proteomic from Mass Spectrometry 5562 proteins Cohort of 74 patients 3. Corresponding Clinical Dataset Event Free Survival	1.Kaplan Meier Survival analysis for genes and proteins in pathways to find prognostic features 2.PROGENy analysis on the TCGA RNA sequencing legacy dataset to find a common core of CRC pathway activities
2019 Prospective CPTAC-COAD Colon Adenocarcinoma	1. Genomic from RNA Sequencing RNA Expression (RSEM-UQ, Log2(Val+1)) 13,482 genes Cohort of 106 patients 2. Proteomic from Mass Spectrometry Protein Expression (TMT, Log2ratio) 6422 proteins Cohort of 96 patients 3. Corresponding Clinical Dataset Cohort of 110 patients 79 patients analysed Event Free Survival	1.Determine the associations between PROGENy pathway activity scores and event free survival 2.Linear Regression Machine Learning models to predict WNT pathway activity