---
license: apache-2.0
---

## Overview
This dataset consists of reference genomes for 10 species:

| Species                  | Assembly Accession                                  |
|--------------------------|-----------------------------------------------------|
| *Arabidopsis thaliana*   | `GCF_000001735.4_TAIR10.1`                          |
| *Caenorhabditis elegans* | `GCF_000002985.6_WBcel235`                          |
| *Danio rerio*            | `GCF_000002035.6_GRCz11`                            |
| *Drosophila melanogaster*| `GCF_000001215.4_Release_6_plus_ISO1_MT`            |
| *Felis catus*            | `GCF_018350175.1_F.catus_Fca126_mat1.0`             |
| *Gallus gallus*          | `GCF_016699485.2_bGalGal1.mat.broiler.GRCg7b`       |
| *Gorilla gorilla*        | `GCF_029281585.2_NHGRI_mGorGor1-v2.0_pri`           |
| *Homo sapiens*           | `GCF_000001405.40_GRCh38.p14`                       |
| *Mus musculus*           | `GCF_000001635.27_GRCm39`                           |
| *Salmo trutta*           | `GCF_901001165.1_fSalTru1.1`                        |

Each item in the dataset contains the following fields:
```
"sequence": datasets.Value("string"),
"species_label": datasets.ClassLabel()  # See below
"description": datasets.Value("string"),
"start_pos": datasets.Value("int32"),
"end_pos": datasets.Value("int32"),
"fasta_url": datasets.Value("string")
```

The class labels are as follows:
| Class                       | Label |
|-----------------------------|-------|
| `'Homo_sapiens'`            |     0 |
| `'Mus_musculus'`            |     1 |
| `'Drosophila_melanogaster'` |     2 |
| `'Danio_rerio'`             |     3 |
| `'Caenorhabditis_elegans'`  |     4 |
| `'Gallus_gallus'`           |     5 |
| `'Gorilla_gorilla'`         |     6 |
| `'Felis_catus'`             |     7 |
| `'Salmo_trutta'`            |     8 |
| `'Arabidopsis_thaliana'`    |     9 |


## Usage
To use this dataset, set the `chunk_length` (length of each sequence, in base-pairs) and the `overlap` (amount each sequence overlaps, in base-pairs).
The dataset only contains a `train` split.
We recommend randomly splitting the dataset to create validation/test sets.
See below for example usage:

```python
import datasets

max_length = 32_768
overlap = 0

dataset = datasets.load_dataset(
  'yairschiff/ten_species',
  split='train',  # original dataset only has `train` split
  chunk_length=max_length,
  overlap=overlap,
  trust_remote_code=True
)
self.dataset = dataset.train_test_split(
  test_size=0.05, seed=42)[split]
```


## Acknowledgments
Code for dataset processing is derived from https://huggingface.co/datasets/InstaDeepAI/multi_species_genomes.