---
license: cc-by-4.0
tags:
  - biology
  - genomics
  - proteomics
  - graph-neural-networks
  - benchmarking
  - omics
pretty_name: OmicsGBench — Omics Graph Benchmark
task_categories:
  - tabular-classification
size_categories:
  - n<1K
---

# OmicsGBench: Benchmarking Graph Neural Networks on Omics Data

OmicsGBench is the first benchmark suite for graph-level prediction in the **n ≪ p regime** characteristic of omics data, where the number of patient samples n is much smaller than the number of nodes (genes or proteins) p per graph.

## Datasets

This repository contains six preprocessed omics graph classification datasets, grouped by modality:

| Dataset | Modality | n | p | Task |
| --- | --- | --- | --- | --- |
| HERITAGE | Proteomics | 654 | 4,976 | Exercise responder (binary) |
| Tuberculosis | Proteomics | 561 | 3,814 | Culture negative vs positive |
| Parkinson's | Transcriptomics | 535 | 21,755 | Cognitive status (binary) |
| AddNeuroMed | Transcriptomics | 711 | 17,197 | Clinical diagnosis (3-class) |
| Smoking | Epigenomics | 464 | 139,125 | Never- vs ever-smoker |
| BRCA | Epigenomics | 640 | 19,049 | Cancer subtype (4-class) |

Tuberculosis is a full-proteome antibody microarray (immunoproteomics), where each feature is one *M. tuberculosis* protein. Smoking stores 139,125 TSS1500/TSS200 methylation probes; training keeps one probe per gene, about 20,763 genes.

## Source Data

- **HERITAGE**: Robbins et al. (2021), *Nature Metabolism*. Available via MoTrPAC Data Hub (motrpac-data.org) under CC-BY 4.0.
- **Tuberculosis**: Kunnath-Velayudhan et al. (2010), *PNAS*. Available via NCBI GEO (GSE19433) under GEO public data access policy.
- **Parkinson's**: Shamir et al. (2017), *Neurology*. Available via NCBI GEO (GSE99039) under GEO public data access policy.
- **AddNeuroMed**: Lovestone et al. (2009). Available via NCBI GEO (GSE63063) under GEO public data access policy.
- **Smoking**: Tsaprouni et al. (2014), *Epigenetics*. Available via NCBI GEO (GSE50660) under GEO public data access policy.
- **BRCA**: Yang et al. (2025), MLOmics, *Scientific Data*. Available on Figshare/Hugging Face under CC-BY 4.0.

## Preprocessing

Datasets share one ingest pipeline: probe-to-gene aggregation where the source is probe-level, and the normalization described in Appendix B of the accompanying paper. Matrices on the Hub are uncorrected. HERITAGE covariate adjustment, AddNeuroMed ComBat, and smoking promoter-probe selection plus median-centering are fit on the training split only.

The default evaluation is stratified 5-fold. A 70/15/15 train/val/test split is available as `split_type=fixed`. Parkinson's and Tuberculosis keep each batch inside one fold: hybridization date for Parkinson's, country of serum collection for Tuberculosis.