Published July 3, 2022 | Version 1
Dataset Open

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

Creators

  • 1. Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
  • 2. Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea; Biomedical Research Institute and Departments of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
  • 3. Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
  • 4. Department of Pediatrics, Seoul National University Children's Hospital, Seoul National University College of Medicine, Seoul, Korea
  • 5. Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
  • 6. Structural Biology Department, Centro Nacional de Investigaciones Oncológicas (CNIO), Madrid, Spain

Description

  • 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.

Files

GEMs_Liver-HCC.zip

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