Systematic analysis of disease-linked rare germline variants reveals new classes of cancer predisposing genes

GEMs_Liver-HCC: 312 cancer patient-specific genome-scale metabolic models (GEMs) for Liver-HCC reconstructed using the RNA-seq data from PCAWG-TCGA Liver-HCC samples and generic human GEM 'Recon 2M.2'

GEMs_Lung-SCC: 493 cancer patient-specific GEMs for Lung-SCC reconstructed using the RNA-Seq data from PCAWG-TCGA Lung-SCC samples and generic human GEM 'Recon 2M.2'

All the patient-specific GEMs were generated using a previously developed method (i.e., tINIT algorithm with a rank-based weight function), which is available at https://bitbucket.org/kaistmbel/recon-manager.