(A) CLIP performs a meta-analysis of datasets from multiple sites for each data modality type: Target addiction score (TAS), Gene dependency (FUNC), protein phosphorylation (PHOS), protein expression (PEXP), gene expression (GEXP), copy number variation (CNV), point mutation (MUT) and methylation (METH) profiles. (B) For each modality type, CLIP iterates over datasets available from multiple sites and quantifies the cancer context specificity (CCS) property for every gene G in cell line j. (C) For all unique cell lines, the CSS property is quantified for each gene G in a dataset D. For continuous modalities (METH, GEXP, PEXP, PHOS, FUNC, TAS), we defined the Outlier Evidence Score (OESG,D,j), calculated by normalizing the observed value by the mean in the dataset for each gene (Xi). SD is defined as the standard deviation. For binary modalities (CNV-GAIN, CNV-LOSS and MUT), we defined the Proportion Score (PSG,D,j) for each gene G in cell line j, calculated as the frequency of the alteration (FD,j) normalized by the total samples in each dataset (ND,j). 