run_TCGAome: Runs the TCGAome analysis pipeline on the given tumor types.
In priesgo/TCGAome: MultiOmics (just RNAseq and RPPA...) Data Analyzer on TCGA data

Runs the TCGAome analysis pipeline on the given tumor types.

run_TCGAome(tumor_types, run_pca_analysis = TRUE,
  run_hclust_analysis = FALSE, run_rgcca = FALSE, run_rcca = FALSE,
  topN = 5, spls_selection_method = "loadings",
  GO_similarity_measure = "Wang", GOA_search_universe = "human",
  enrichment_significance_thr = 0.01, GO_ontology = "BP",
  multiple_test_adjustment = FALSE)

`tumor_types`	Vector of tumor types to be analyzed from those available at TCGA (run RTCGAToolbox::getFirehoseDatasets() to see all available types)
`run_pca_analysis`	Flag indicating if the PCA should run, this is part of the data pre-analysis (default: TRUE)
`run_hclust_analysis`	Flag indicating if the hierarchical clustering analysis should run, this is part of the data pre-analysis (default: FALSE)
`run_rgcca`	Flag indicating if the Regularized Generalized Canonical Correlation Analysis (RGCCA) should run (default: FALSE). Beware that this analysis is not intended for datasets with number of variables >> number of samples.
`run_rcca`	Flag indicating if the Regularized Canonical Correlation Analysis (rCCA) should run (default: FALSE). Beware that this analysis is not intended for datasets with number of variables >> number of samples.
`topN`	Indicates the top number of variables to select on MCIA and sPLS results (default: 5). It will select N variables on each of the data types, on each of the three first components and on each extreme of range, that is a maximum of 232*N, considering that there might be overlap between components.
`spls_selection_method`	Indicates the method for variable selection on sPLS results. One of 'correlation' or 'loadings' (default: 'loadings'). Loadings method will choose those variables maximizing variance across the samples, while correlation method will choose those variables with a higher correlation with other variables, that is those variables more distant to the origin in the correlation plot.
`GO_similarity_measure`	The similarity measured employed to cluster and visualize GO terms, one in 'Resnik', 'Lin', 'Rel', 'Jiang', 'Wang', 'UI', 'binary', 'bray-curtis', 'cosine', 'all' (default: 'Wang')
`GOA_search_universe`	The GOA universe to use in functional similarity measures (i.e.: only aplicable to 'binary', 'bray-curtis', 'cosine', 'UI'), one in 'human', 'uniprot', 'gene_list' (default: 'human')
`enrichment_significance_thr`	The threshold to consider a GO enrichment result as significant (default: 0.01)
`GO_ontology`	The GO ontology on which to perform the enrichment, one of 'BP', 'MF', 'CC' (default: BP)
`multiple_test_adjustment`	Flag to run multiple test adjustment on GO enrichment results (default: F)