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

<ul> <li>GEMs_Liver-HCC: 312&nbsp;cancer patient-specific genome-scale metabolic models (GEMs) for Liver-HCC reconstructed using the&nbsp;RNA-seq&nbsp;data from&nbsp;PCAWG-TCGA Liver-HCC samples and&nbsp;generic human GEM &#39;Recon 2M.2&#39;</li> <li>GEMs_Lung-SCC: 493 cancer patient-specific GEMs&nbsp;for Lung-SCC&nbsp;reconstructed using the RNA-Seq data from PCAWG-TCGA Lung-SCC samples&nbsp;and&nbsp;generic human GEM &#39;Recon 2M.2&#39;</li> </ul> <p>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&nbsp;<a href="https://bitbucket.org/kaistmbel/recon-manager">https://bitbucket.org/kaistmbel/recon-manager</a>.</p>