File size: 10,443 Bytes
6884927
 
 
 
 
 
3d66834
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c023648
b2df15b
baad5cf
c023648
 
 
 
b2df15b
3d66834
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
---
tags:
- DNA
- Genomics
- Nucleotide
pretty_name: Human Reference Genome
---
# Dataset Card for the human reference genome

## Dataset Description

- **Repository:** [Nucleotide Transformer](https://github.com/instadeepai/nucleotide-transformer)
- **Paper:** [The Nucleotide Transformer: Building and Evaluating Robust Foundation Models for Human Genomics](https://www.biorxiv.org/content/10.1101/2023.01.11.523679v1)

### Dataset Summary

The Human reference genome dataset was constructed by considering all autosomal and sex chromosomes sequences from reference assembly [GRCh38/hg38](https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.26) and reaches a total of 3.2 billion nucleotides.

### Supported Tasks and Leaderboards

This dataset has been used as a pre-training corpus for the Nucleotide Transformers models. Depending on the configuration used, each sequence is 6,200 or 12,200 base pase pairs long. If the dataset is iterated without being shuffled, the first 100 nucleotides of a sequence are the same as the last 100 base pairs of the previous sequence, and the last 100 nucleotides are the same as the first 100 base pairs of the next sequence. During training, this allows for randomly selecting a nucleotide between the first 200 nucleotides of the sequence and start the tokenization from this nucleotide. That way, all the chromosome is covered and the model sees different tokens for a given sequence at each epoch. 

### Languages

DNA

## Dataset Structure

[N/A]


### Data Instances

For each instance, there is a string representing the sequence, a string indicating the chromosome, and two integers representing the index of the first and last nucleotide respectively. An instance is shown below:
```python
{'sequence': 'CATCTGCAGGTGTCTGACTTCCAGCAACTGCTGGCCTGTGCCAGGGTGCAAGCTGAGCACTGGAGTGGAGTTTTCCTGTGGAGAGGAGCCATGCCTAGAGTGGGATGGGCCATTGTTCATCTTCTGGCCCCTGTTGTCTGCATGTAACTTAATACCACAACCAGGCATAGGGGAAAGATTGGAGGAAAGATGAGTGAGAGCATCAACTTCTCTCACAACCTAGGCCAGTAAGTAGTGCTTGTGCTCATCTCCTTGGCTGTGATACGTGGCCGGCCCTCGCTCCAGCAGCTGGACCCCTACCTGCCGTCTGCTGCCATCGGAGCCCAAAGCCGGGCTGTGACTGCTCAGACCAGCCGGCTGGAGGGAGGGGCTCAGCAGGTCTGGCTTTGGCCCTGGGAGAGCAGGTGGAAGATCAGGCAGGCCATCGCTGCCACAGAACCCAGTGGATTGGCCTAGGTGGGATCTCTGAGCTCAACAAGCCCTCTCTGGGTGGTAGGTGCAGAGACGGGAGGGGCAGAGCCGCAGGCACAGCCAAGAGGGCTGAAGAAATGGTAGAACGGAGCAGCTGGTGATGTGTGGGCCCACCGGCCCCAGGCTCCTGTCTCCCCCCAGGTGTGTGGTGATGCCAGGCATGCCCTTCCCCAGCATCAGGTCTCCAGAGCTGCAGAAGACGACGGCCGACTTGGATCACACTCTTGTGAGTGTCCCCAGTGTTGCAGAGGTGAGAGGAGAGTAGACAGTGAGTGGGAGTGGCGTCGCCCCTAGGGCTCTACGGGGCCGGCGTCTCCTGTCTCCTGGAGAGGCTTCGATGCCCCTCCACACCCTCTTGATCTTCCCTGTGATGTCATCTGGAGCCCTGCTGCTTGCGGTGGCCTATAAAGCCTCCTAGTCTGGCTCCAAGGCCTGGCAGAGTCTTTCCCAGGGAAAGCTACAAGCAGCAAACAGTCTGCATGGGTCATCCCCTTCACTCCCAGCTCAGAGCCCAGGCCAGGGGCCCCCAAGAAAGGCTCTGGTGGAGAACCTGTGCATGAAGGCTGTCAACCAGTCCATAGGCAAGCCTGGCTGCCTCCAGCTGGGTCGACAGACAGGGGCTGGAGAAGGGGAGAAGAGGAAAGTGAGGTTGCCTGCCCTGTCTCCTACCTGAGGCTGAGGAAGGAGAAGGGGATGCACTGTTGGGGAGGCAGCTGTAACTCAAAGCCTTAGCCTCTGTTCCCACGAAGGCAGGGCCATCAGGCACCAAAGGGATTCTGCCAGCATAGTGCTCCTGGACCAGTGATACACCCGGCACCCTGTCCTGGACACGCTGTTGGCCTGGATCTGAGCCCTGGTGGAGGTCAAAGCCACCTTTGGTTCTGCCATTGCTGCTGTGTGGAAGTTCACTCCTGCCTTTTCCTTTCCCTAGAGCCTCCACCACCCCGAGATCACATTTCTCACTGCCTTTTGTCTGCCCAGTTTCACCAGAAGTAGGCCTCTTCCTGACAGGCAGCTGCACCACTGCCTGGCGCTGTGCCCTTCCTTTGCTCTGCCCGCTGGAGACGGTGTTTGTCATGGGCCTGGTCTGCAGGGATCCTGCTACAAAGGTGAAACCCAGGAGAGTGTGGAGTCCAGAGTGTTGCCAGGACCCAGGCACAGGCATTAGTGCCCGTTGGAGAAAACAGGGGAATCCCGAAGAAATGGTGGGTCCTGGCCATCCGTGAGATCTTCCCAGGGCAGCTCCCCTCTGTGGAATCCAATCTGTCTTCCATCCTGCGTGGCCGAGGGCCAGGCTTCTCACTGGGCCTCTGCAGGAGGCTGCCATTTGTCCTGCCCACCTTCTTAGAAGCGAGACGGAGCAGACCCATCTGCTACTGCCCTTTCTATAATAACTAAAGTTAGCTGCCCTGGACTATTCACCCCCTAGTCTCAATTTAAGAAGATCCCCATGGCCACAGGGCCCCTGCCTGGGGGCTTGTCACCTCCCCCACCTTCTTCCTGAGTCATTCCTGCAGCCTTGCTCCCTAACCTGCCCCACAGCCTTGCCTGGATTTCTATCTCCCTGGCTTGGTGCCAGTTCCTCCAAGTCGATGGCACCTCCCTCCCTCTCAACCACTTGAGCAAACTCCAAGACATCTTCTACCCCAACACCAGCAATTGTGCCAAGGGCCATTAGGCTCTCAGCATGACTATTTTTAGAGACCCCGTGTCTGTCACTGAAACCTTTTTTGTGGGAGACTATTCCTCCCATCTGCAACAGCTGCCCCTGCTGACTGCCCTTCTCTCCTCCCTCTCATCCCAGAGAAACAGGTCAGCTGGGAGCTTCTGCCCCCACTGCCTAGGGACCAACAGGGGCAGGAGGCAGTCACTGACCCCGAGACGTTTGCATCCTGCACAGCTAGAGATCCTTTATTAAAAGCACACTGTTGGTTTCTGCTCAGTTCTTTATTGATTGGTGTGCCGTTTTCTCTGGAAGCCTCTTAAGAACACAGTGGCGCAGGCTGGGTGGAGCCGTCCCCCCATGGAGCACAGGCAGACAGAAGTCCCCGCCCCAGCTGTGTGGCCTCAAGCCAGCCTTCCGCTCCTTGAAGCTGGTCTCCACACAGTGCTGGTTCCGTCACCCCCTCCCAAGGAAGTAGGTCTGAGCAGCTTGTCCTGGCTGTGTCCATGTCAGAGCAACGGCCCAAGTCTGGGTCTGGGGGGGAAGGTGTCATGGAGCCCCCTACGATTCCCAGTCGTCCTCGTCCTCCTCTGCCTGTGGCTGCTGCGGTGGCGGCAGAGGAGGGATGGAGTCTGACACGCGGGCAAAGGCTCCTCCGGGCCCCTCACCAGCCCCAGGTCCTTTCCCAGAGATGCCTGGAGGGAAAAGGCTGAGTGAGGGTGGTTGGTGGGAAACCCTGGTTCCCCCAGCCCCCGGAGACTTAAATACAGGAAGAAAAAGGCAGGACAGAATTACAAGGTGCTGGCCCAGGGCGGGCAGCGGCCCTGCCTCCTACCCTTGCGCCTCATGACCAGCTTGTTGAAGAGATCCGACATCAAGTGCCCACCTTGGCTCGTGGCTCTCACTGCAACGGGAAAGCCACAGACTGGGGTGAAGAGTTCAGTCACATGCGACCGGTGACTCCCTGTCCCCACCCCCATGACACTCCCCAGCCCTCCAAGGCCACTGTGTTTCCCAGTTAGCTCAGAGCCTCAGTCGATCCCTGACCCAGCACCGGGCACTGATGAGACAGCGGCTGTTTGAGGAGCCACCTCCCAGCCACCTCGGGGCCAGGGCCAGGGTGTGCAGCACCACTGTACAATGGGGAAACTGGCCCAGAGAGGTGAGGCAGCTTGCCTGGGGTCACAGAGCAAGGCAAAAGCAGCGCTGGGTACAAGCTCAAAACCATAGTGCCCAGGGCACTGCCGCTGCAGGCGCAGGCATCGCATCACACCAGTGTCTGCGTTCACAGCAGGCATCATCAGTAGCCTCCAGAGGCCTCAGGTCCAGTCTCTAAAAATATCTCAGGAGGCTGCAGTGGCTGACCATTGCCTTGGACCGCTCTTGGCAGTCGAAGAAGATTCTCCTGTCAGTTTGAGCTGGGTGAGCTTAGAGAGGAAAGCTCCACTATGGCTCCCAAACCAGGAAGGAGCCATAGCCCAGGCAGGAGGGCTGAGGACCTCTGGTGGCGGCCCAGGGCTTCCAGCATGTGCCCTAGGGGAAGCAGGGGCCAGCTGGCAAGAGCAGGGGGTGGGCAGAAAGCACCCGGTGGACTCAGGGCTGGAGGGGAGGAGGCGATCTTGCCCAAGGCCCTCCGACTGCAAGCTCCAGGGCCCGCTCACCTTGCTCCTGCTCCTTCTGCTGCTGCTTCTCCAGCTTTCGCTCCTTCATGCTGCGCAGCTTGGCCTTGCCGATGCCCCCAGCTTGGCGGATGGACTCTAGCAGAGTGGCCAGCCACCGGAGGGGTCAACCACTTCCCTGGGAGCTCCCTGGACTGGAGCCGGGAGGTGGGGAACAGGGCAAGGAGGAAAGGCTGCTCAGGCAGGGCTGGGGAAGCTTACTGTGTCCAAGAGCCTGCTGGGAGGGAAGTCACCTCCCCTCAAACGAGGAGCCCTGCGCTGGGGAGGCCGGACCTTTGGAGACTGTGTGTGGGGGCCTGGGCACTGACTTCTGCAACCACCTGAGCGCGGGCATCCTGTGTGCAGATACTCCCTGCTTCCTCTCTAGCCCCCACCCTGCAGAGCTGGACCCCTGAGCTAGCCATGCTCTGACAGTCTCAGTTGCACACACGAGCCAGCAGAGGGGTTTTGTGCCACTTCTGGATGCTAGGGTTACACTGGGAGACACAGCAGTGAAGCTGAAATGAAAAATGTGTTGCTGTAGTTTGTTATTAGACCCCTTCTTTCCATTGGTTTAATTAGGAATGGGGAACCCAGAGCCTCACTTGTTCAGGCTCCCTCTGCCCTAGAAGTGAGAAGTCCAGAGCTCTACAGTTTGAAAACCACTATTTTATGAACCAAGTAGAACAAGATATTTGAAATGGAAACTATTCAAAAAATTGAGAATTTCTGACCACTTAACAAACCCACAGAAAATCCACCCGAGTGCACTGAGCACGCCAGAAATCAGGTGGCCTCAAAGAGCTGCTCCCACCTGAAGGAGACGCGCTGCTGCTGCTGTCGTCCTGCCTGGCGCCTTGGCCTACAGGGGCCGCGGTTGAGGGTGGGAGTGGGGGTGCACTGGCCAGCACCTCAGGAGCTGGGGGTGGTGGTGGGGGCGGTGGGGGTGGTGTTAGTACCCCATCTTGTAGGTCTGAAACACAAAGTGTGGGGTGTCTAGGGAAGAAGGTGTGTGACCAGGGAGGTCCCCGGCCCAGCTCCCATCCCAGAACCCAGCTCACCTACCTTGAGAGGCTCGGCTACCTCAGTGTGGAAGGTGGGCAGTTCTGGAATGGTGCCAGGGGCAGAGGGGGCAATGCCGGGGCCCAGGTCGGCAATGTACATGAGGTCGTTGGCAATGCCGGGCAGGTCAGGCAGGTAGGATGGAACATCAATCTCAGGCACCTGGCCCAGGTCTGGCACATAGAAGTAGTTCTCTGGGACCTGCAAGATTAGGCAGGGACATGTGAGAGGTGACAGGGACCTGCAGGGGCAGCCAACAAGACCTTGTGTGCACCTCCCATGGGTGGAATAAGGGGCCCAACAGCCTTGACTGGAGAGGAGCTCTGGCAAGGCCCTGGGCCACTGCACCTGTCTCCACCTCTGTCCCACCCCTCCCACCTGCTGTTCCAGCTGCTCTCTCTTGCTGATGGACAAGGGGGCATCAAACAGCTTCTCCTCTGTCTCTGCCCCCAGCATCACATGGGTCTTTGTTACAGCACCAGCCAGGGGGTCCAGGAAGACATACTTCTTCTACCTACAGAGGCGACATGGGGGTCAGGCAAGCTGACACCCGCTGTCCTGAGCCCATGTTCCTCTCCCACATCATCAGGGGCACAGCGTGCACTGTGGGGTCCCAGGCCTCCCGAGCCGAGCCACCCGTCACCCCCTGGCTCCTGGCCTATGTGCTGTACCTGTGTCTGATGCCCTGGGTCCCCACTAAGCCAGGCCGGGCCTCCCGCCCACACCCCTCGGCCCTGCCCTCTGGCCATACAGGTTCTCGGTGGTGTTGAAGAGCAGCAAGGAGCTGACAGAGCTGATGTTGCTGGGAAGACCCCCAAGTCCCTCTTCTGCATCGTCCTCGGGCTCCGGCTTGGTGCTCACGCACACAGGAAAGTCCTTCAGCTTCTCCTGAGAGGGCCAGGATGGCCAAGGGATGGTGAATATTTGGTGCTGGGCCTAATCAGCTGCCATCCCATCCCAGTCAGCCTCCTCTGGGGGACAGAACCCTATGGTGGCCCCGGCTCCTCCCCAGTATCCAGTCCTCCTGGTGTGTGACAGGCTATATGCGCGGCCAGCAGACCTGCAGGGCCCGCTCGTCCAGGGGGCGGTGCTTGCTCTGGATCCTGTGGCGGGGGCGTCTCTGCAGGCCAGGGTCCTGGGCGCCCGTGAAGATGGAGCCATATTCCTGCAGGCGCCCTGGAGCAGGGTACTTGGCACTGGAGAACACCTGTGGACACAGGGACAAGTCTGAGGGGGCCCCAAGAGGCTCAGAGGGCTAGGATTGCTTGGCAGGAGAGGGTGGAGTTGGAAGCCTGGGCGAGAAGAAAGCTCAAGGTACAGGTGGGCAGCAGGGCAGAGACTGGGCA',
 'chromosome': '1',
 'start_pos': 12000,
 'end_pos': 18200}
```

### Data Fields

- `sequence`: a string containing a DNA sequence from the human reference genome
- `chromosome`: a string indicating the chromosome (1,2,...,21,X,Y)
- `start_pos`: an integer indicating the index of the sequence's first nucleotide 
- `end_pos`: an integer indicating the index of the sequence's last nucleotide 

### Data Splits

The Human reference genome dataset has 3 splits: train, validation, and test. Below are the statistics for the dataset.
```
| Dataset Split | Number of Instances in Split (6kb)          |  Number of Instances in Split (12kb)                           |
| ------------- | ------------------------------------------- | -------------------------------------------------------------- |
| Train         | 498,444                                     | 249,222                                                        |
| Validation    | 7,784                                       | 3,892                                                          |
| Test          | 8,469                                       | 4,234                                                          |
```
## Dataset Creation

[N/A]

### Curation Rationale

[N/A]


### Source Data

#### Initial Data Collection and Normalization



The data consists of sequences cut from the chromosomes found in the [GRCh38/hg38](https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.26) human reference genome.

#### Who are the source language producers?

[N/A]

### Annotations

The dataset does not contain any additional annotations.

#### Annotation process

[N/A]

#### Who are the annotators?

[N/A]

### Personal and Sensitive Information

[N/A]

## Considerations for Using the Data

### Social Impact of Dataset

[N/A]

### Discussion of Biases

[N/A]


### Other Known Limitations

[N/A]


## Additional Information

### Dataset Curators

[N/A]


### Licensing Information

[N/A]

### Citation Information

```bibtex
@article{dalla2023nucleotide,
  title={The Nucleotide Transformer: Building and Evaluating Robust Foundation Models for Human Genomics},
  author={Dalla-Torre, Hugo and Gonzalez, Liam and Mendoza Revilla, Javier and Lopez Carranza, Nicolas and Henryk Grywaczewski, Adam and Oteri, Francesco and Dallago, Christian and Trop, Evan and Sirelkhatim, Hassan and Richard, Guillaume and others},
  journal={bioRxiv},
  pages={2023--01},
  year={2023},
  publisher={Cold Spring Harbor Laboratory}
}
```