HyperNetWalk: data and reference networks

This repository contains the supporting data for HyperNetWalk, an unsupervisedhypergraph-based framework for personalized and cohort-level cancer driver geneidentification via reverse inference on a layered signaling–regulatory network. These files are too large to host on GitHub and are archived here. The sourcecode is available at: https://github.com/xqxu921/HyperNetWalk Contents (download what you need and unzip into the `data/` directory of theHyperNetWalk repository): - network_reference.zip — PPI/GRN/TF–target networks and gene annotation (STRINGv12.txt, 9606.protein.links.v12.0.onlyAB.tsv, RegNet_human_V2.txt, gencode.v36.annotation.gtf.gene.probemap, omnipath_interactions.tsv). Required to run the model. Unzip into data/. - processed_data.zip — Preprocessed model inputs (mutation and expression matrices) for 12 TCGA cancer types (BRCA, COAD, HNSC, KIRC, KIRP, LIHC, LUAD, LUSC, PRAD, STAD, THCA, UCEC). Unzip into data/processed_data/. - rawdata.zip — TCGA raw files (somatic mutation, expression counts/TPM, survival) per cancer type, for full reproduction from raw data. Unzip into data/rawdata/. See the repository README for usage instructions. If you use these data,please cite the associated manuscript (in preparation) and this record.