---
license: mit
language:
- en
dataset_info:
  - name: Orthoformer
    description: Large-scale datasets for training and evaluating the Orthoformer foundation model for orthology and protein family representation learning.
    config_name: default
    splits:
      - name: foundation_model_dataset
        num_examples: 3000000
      - name: Downstream_Tasks_dataset
      - name: Orthoformer_eval_dataset
tags:
- protein
- orthology
- foundation-model
- bioinformatics
- embeddings
---

# Orthoformer Datasets

## 📌 Overview

**Orthoformer** is a large-scale genomics dataset designed to support **function-centric foundation modeling** of microbial and viral genomes.

Unlike conventional sequence-based models that infer biological roles from nucleotide or protein context, Orthoformer represents each genome by its **orthologous group composition and abundance**, treating **functional units rather than sequences** as the basic biological vocabulary.

The dataset was constructed from approximately **three million prokaryotic and viral genomes**, each encoded as a high-dimensional functional profile capturing:

- biochemical identity  
- gene family dynamics  
- evolutionary conservation  
- pathway-scale metabolic capacity  

These representations enable learning a **functional embedding space** that provides an **alignment-free measure of genomic similarity**, supporting robust taxonomy, phylogenetic analysis, and detection of functional convergence across microbial lineages.

The same functional embeddings generalize beyond evolutionary structure to predict:

- biosynthetic gene cluster abundance  
- ecological niche differentiation  
- organism-level phenotypes  
- marker-gene associations  

Together, the Orthoformer dataset establishes a **function-first framework for microbial genomics**, offering a scalable alternative to sequence-centric datasets for studying microbial evolution, function, and ecology.


---

## 📂 Dataset Structure

The repository is organized into three functional splits:

| Split | Purpose | Description |
|------|--------|-------------|
| `foundation_model_dataset` | Pretraining | Large-scale collection of microbial and viral genomes represented by orthologous group composition and abundance, used for self-supervised function-centric foundation model training |
| `Downstream_Tasks_dataset` | Fine-tuning | Labeled genome-level datasets for functional, metabolic, and ecological prediction tasks, including niche, biosynthetic capacity, and phenotype inference |
| `Orthoformer_eval_dataset` | Evaluation | Benchmark datasets for evaluating functional embeddings on taxonomy, phylogeny, functional convergence, and biological consistency |

---

## 📊 Dataset Statistics

| Split | Size | Max Sequence Length |
|------|------|--------------------|
| foundation_model_dataset | ~3M sequences | 2048 |
| Downstream_Tasks_dataset | Task dependent | Task dependent |
| Orthoformer_eval_dataset | Benchmarks | Task dependent |

---

## 🚀 Accessing the Dataset

You can download the dataset via Hugging Face using **Git + Xet (recommended for large files)**:

```bash
# Install git-xet (Linux)
curl -sSf https://raw.githubusercontent.com/huggingface/xet-core/main/git_xet/install.sh | sh
git xet install

# Clone the dataset
git clone https://huggingface.co/datasets/jackkuo/Orthoformer
````

If you only want the metadata without large files:

```bash
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/datasets/jackkuo/Orthoformer
```

---

## 🧬 Intended Use

The Orthoformer dataset is intended for training and evaluating **foundation models for microbial functional genomics**, including:

- Functional embedding of microbial and viral genomes  
- Alignment-free phylogeny and taxonomy  
- Functional convergence and evolutionary analysis  
- Metabolic and pathway-level phenotype prediction  
- Biosynthetic gene cluster and ecological niche inference  

It is specifically designed for **function-centric modeling**, where orthologous gene groups are treated as the fundamental representation units instead of raw nucleotide or amino acid sequences.

---

## 📜 License

This dataset is released under the **MIT License**.

---

## 📖 Citation

If you use this dataset, please cite:

```bibtex
@dataset{xxx,
  title = {Orthoformer: xxx},
  author = {xxx},
  year = {2025},
}
```

---

## 🔗 Related Resources

* **Model**: [https://huggingface.co/jackkuo/Orthoformer](https://huggingface.co/jackkuo/Orthoformer)
* **Code**: [https://github.com/JackKuo666/Orthoformer](https://github.com/JackKuo666/Orthoformer)

---