InstaDeepAI/plant-multi-species-genomes

Paper: A Foundational Large Language Model for Edible Plant Genomes

Dataset Summary

The Plant Multi Species dataset was constructed by parsing plant genomes available on NCBI. In total there are 48 different plant species contained in the dataset.

This dataset has been used as a pre-training corpus for the AgroNT model. Each sequence is 6,200 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.

Example Usage

from datasets import load_dataset

dataset = load_dataset('InstaDeepAI/plant-multi-species-genomes') ### Will use the default chunk length of 6000bp

# or

chunk_length = 10000
dataset = load_dataset('InstaDeepAI/plant-multi-species-genomes',chunk_length=chunk_length) ### Will use your desired chunk length(in this case 10000bp)

Data Instances

For each instance, there is a string representing the sequence, a string indicating the description of the sequence, two integers representing the index of the first and last nucleotide respectively. An instance is shown below:

{'sequence': 'CCAAATAGTTGATACTACTTGCCCATGGGTTTCAAAGGTATTTGTTTCCCTTTTCTATCAGAGTAGAGAATAAGGTCTTGGATTTCCCTTGAATATCTTTTTCATAAATAATGTGTTAATTTCCACTAAAGGTCTGGAACTCTGTTGAGAAGCACAAGAAGGGTGATTACACTTCAATCATACATGGTAAATATTCACACGAAGAGACTATTGCAACAGCCTCATTTGCAGGAAGATATATTGTCGTAAAGAACATGACTGAGGTAACGATTTGTTAATTAATAATCAGTTTATTGTGAATCATATTTACAAATAAACGTTTTTTACTACCATTTTCTGTTAAAAAAACAGGCAATGTATGTATGCGATTACATTCTTGGTGGGGAATTAGATGGGTCTAGCTCTACAAGAGAAGCATTTCTTGAGGTATATTGATTCTTTTCTTCCATAATATTTGCACAAAAGAAAATAAGATTTAAAAATGTGTCCATGTGTTGCAGAAATTCAAAAACGCTATTTCTGCGGGATTTGATCCAGATGTTGACTTAGCTAAAGTTGGCATTGCAAATCAAACCACGATGCTCAAGGGTGAAACAGAGGAGATAGGTAAGTTTAATGTTTGCAATGCTTACTGTTTCTATCCAATTCTAAATATAGTGTTCAAGTAAACACTGAAATTTCAGGTAAATTGGTTGAGAAGACCATGATGCGCAAACACGGTGTAGAGAATGCCAATGATCATTTTGTCAGCTTCAACACCATATGTGATGCTACCCAGGTAGGCTTACTGATTTTTTTTTTTCCTTTTTTGTTTTTCTAATTGGAATATTCAATTCAAAATTTAAACTGCTAAGGTATTGTTTTTCTCCTTTACATTTTGTTAAATCCATGCAATTCACTCATTCCCACTTTTTCATAACCTTTTAAACCTCATTTATCATACCATCTACTTACTCTTTAGATTTGCAAATTAGAGCACTGCAATTTCTGTGGAAGTGAACCAAAAGCGAAAGGGGATAGAATACTTTCATGTGATTGAATTTTATAGTCCCTTTTGTATTAATCTATTCAATTGCTGGTTTAGTTTCCCCTTATCACATTCTCTTGCACAACTTCAGGAAAGGCAAGATGCTATGTTCAAGCTGGTGGAAGAGAAACTCGATCTTATTCTGGTCGTTGGTGGGTGGAACTCCAGTAATACTTCACATCTCCAAGAGATCGCAGAGCTCAAGGGAATCCCGTCCTACTGGATTGACAATGAACAGAGAATTGGACCAGGAAACAAGATCACCTATAAGTTAAATGTATGTTGTACACGCGCAGTTTGTATAATTATTTATATTGCGAACTTGATGATTTTAATTATCATCTTATCTGTTTGTACAAACGCAGCATGGAGAGCTGGTCGAGAAAGAAAATTGGCTTCCTGCTGGACCAATCACTATTGGTGTCACCTCAGGGGCTTCTACTCCTGACAAGGTATATATATTAATTCAAGAGTTGAAAAATCCCTTGGTTAAAGTATTAAGTCGCGGGATCTCCTTCATCTTATTAACAATTTCCACATGGCTTATGCAGGTCGTGGAGGAAGCATTGGGCAAGGTCTTTGACATTAAAAGCCAAGAAGCTCTGCAAGCGGCATAAATTGAGAGGACTTGAGCAGTGTTTTGAGCTGAAGTATCACTATCGCTTAACTTGTACGGTACTAGAAATGGGATTGCATAAGAGCACTCCCTTATCGACAGGAAATGCTGCAGTCCAAAATCTATCCTGCCATTATTATTTTATTTTATTTTATTTTGTTTTGTTTTATTTTTGTGTTGTGACATTAATTTATGCATGCTGGTCAAGGCCTGGTTGAGCCCAGCGAGTTCTCTCACCCAATCCATTTTACAAAATGGTCTGATAAAGTTATGATATTGTTTTGCGGTTTAATTATCCGGATTCCAGCAGCATCCTTGTTATGATATTATCATTTTAACAGTAAAAAAATAAAATAAAGTGTGTTATATTTAAAATAAAGAGATATTGCATTAAATACATTTTTTTTAAAAAAAACATTATGATAATTTGAATTATGCTAACTTAATTATAACGGGTGAAACTTAAGAATCACATATAATCAGTGGTGGATCTAGATAAAAAAAGAAGAGGGTATTAGAAGAAAAGAATTGAAGTTTGTCTTCCTTCACTATCCGACTGTAGCATATTAATAGAATTTTTTAAAAACAAGAGGTACTCAAGCACATCTCCGCGCTCCTAGATCCATCACTGCATATAACAACAATGAAATAAATCATTTTACTTTTTTTCATCAACTCTCCATTTGCTTAACGTTAGCCGTATAAGATAGCACGTGATGGAGAGCTTCTCGATTTTTTAAATTATTTTGTAAGAGCCATAAAATATTATTTAAATTAAATAATTATTTTATATTTAAAAATAATGATTTATTTTTTAAAAAAGAACTAGAGAGCGAGAGACAGCGTACAGGATTCTTTTTCTAATTATTCCGGCCCAGAAACCTGCTTCTTCGAGTTATTAGAGGGACCCTCAGCTTACCTTATACGGAGAGCAGCCTGGACGGTGTCTGAACGAGAACGGAGAAAGATGCAAAGCCAGCGAACAACACAAAACAAAGGCCGAGATCTCCAAACCCCATAACCCTACCTTAAACCCATGATCACAACTAGATTCTTCCCTCATTCGCGTTTCTTCCTCCCCTCGCACCTGCCCACTCTCTGCCGGCCCATCCACTCCGGCGCTGCCCACCCCCGCATCACCAGATCTGAGCTCGTCGACCGGATATGCCGCATCCTCACCCTCGAGCGCTTCCACGCCATTCCCAAGCTTCCCTTCCGCTTCTCCGACGATCTCCTCGACGCCGTCCTCGTCAGGCTGCGCCTCGACGCCGACGCCTGCCTGGGCTTCTTCCGGATCGCACTGAGGCAGCAGTACTTCAGGCCCAACGCGGAATCTTATTGCAGAATTGTCCACATTTTGTCTCGAGCACGCATGTTCGACGATGCGAGAGGGTTGTTGAGGGAATTGGTGGCGATGATGAGCTCGGCTAGCCCGGAGCCGTCTGTCTCTTTTGTTTTTGATCGGATGGTTAAGGTGTACAAGGAGTTCACTTTCTCTCCTACGGTGTTTGACATGCTCCTGAAGGCTTATGCTGAGGGTGGATTGCGAAAGGAGGCTCTTTTTGTGTTTGATAATATGGGGAAATGCGGATGTCAGCCTAGTTTGAAGTCCTGCAACAGCCTTTTGAGTAGTTTGGTTAAAGGAGGGGATATTAACGCGGCAATTCTAGTTTATGAACAGATGTGCAAAGCTGGGATATTACCTGATGTTTTCACAACGTCTATAATAGTTAATGCCTATTGTAAGGGTGGAAATCTAGAGAAAGCCTTGAGCTTTGTGGCAGAGATGGAAAGGAAGGGGTTTGATGTTAATATTGTGACTTTCCATTCTCTGATCAATGGGTACTGTAGTTTGGGCCAGACGGAAGCGGCACTCAAGGTGTTCGACATGATGACTAAAAGAGGGATTTTGCCAAATGTTGTCTCTTTTACTTTGTTGATTAAGGGTTACTGCAAAGAAGGCAAGGTTAAGGAAGCCGAGAAAGCCCTTGTTGACATGAAACAGCTCCATGGTTTGAGTCCTGACGAAGTTGCTTACGGTGTGCTAATTAACATTCATTGCCAAATGGGGGGAATGGATGATGCAATGAGAATCCGGGATAAAATGTTGAGTGAAGGGATGAAGGAAAACATATTTATTTGTAATGCAATGATCAATGGGTATTGCAAGTCCGGAAGAATTGAGGAAGCAGAGATTTTGCTTTTCGATATGGAGAAGGGTCATCTAAAACCAGACTCCTACAGTTACAATTCTCTATTAGATGGGTATTGCAAGAAGGGTCTTATGAGAGATGCTTTTGGAATATGTGACAGGATGATAAGGAATGGAGTCGAAGTTACAGTTATAACTTATAATGCACTATTTAAAGGCTTTTGTCTGTCAGGTGCAATAGATCATGCCCTGAACTTGTGGTTTTTGATGCTGAAAAGAGCTGTTGCTCCAAATGAGATTAGCTGTTCCACATTGTTGGATGGGTTCTTCAAATCAAGGAATTATGAACAAGCCTTGAAATTTTGGAATGAGATACTAGCTAGGGGATTCACAAAGAACCAAATAACATTCAATACAGTGATAAATGGTTTTTGTAAAGCAGGGAAAATATCTGAGGCGGTGAATATTATGGAAAAGATGAAGGCCTGGGGATGTCCTCCTGATAGCATTACTTACAGGACATTGATTGACGGTTATTGTAAACTTGGTGATGTGGAGCAAGCTCTTAAGTTATGGAATGAGATGGAACCTTCTGGGTTTTCTCCTTCAATCGAAATGTTCAATTCTCTTATTTCTGGGCACTTCATAGCTAATGGTTCTGATAGGATTGATGGCCTTCTAACTAATATGCACAAGAGTGGACTGACTCCCAACATAGTTACTTATGGAATTCTGATTGCTGGATGGTGCAGAGAAGGAATGTTGGATAGGGCTTTTGATATATATTTTGAAATGGTTGCCAAAGGCTTAACTCCAAATACATACATATGCAGTGCCCTTGTTAGTGGTCTTTATAGACAGGGTAAGATTGACGAGGCAAATGCTATATTGGCAAAAATTGTGGATGCTAGCATGCTTCCAAAGTATGAAAATTCTGATAAGTACCTTAAGTGTGTTACGAACAATATCTACCATCACGAAATCACAAATCTGCTCGCTCAGTCTAAAAATGAGAATCTCCTGCCTAACAACATTATCTATAATGTTATTATTTGCGGTCTTTGCAAATCTGGAAGGATTTTGGATGCAAAACAATTTTTTGCAGACTTGTTGCAGAGGGGTTTTGTTCCAGACAATTTTACTTACAGTAATCTTATTCATGGCTATTCAGCAGCTGGCAATATAGATCAGGCTTTTCAATTAAGGGATGAAATGATTAAAAAGGGCCTCTTTCCCAATATTATAACATACAATTCTCTCATCAATGGTCTCTGCATATCTGGAAATTTAGATAGAGCTGTCAATCTATTCAACAAGCTGCAGTCAAAAGGTTTAGCACCGAATGTTATTACATTCAACACATTGATTGATGGATTCTGCAGAGTTGGTAATCTAACAGAAGCATTCAAGCTGAAATATAAGATGATAGAGGCAGGAATTTATCCCAATGTTGTTACGTATTCTACACTAATTAATGGCCTTTGTTGCCAAGGGGAAATGGAAGCATCCATCAAACTCCTGGATCAAATGATTAGTAGTGGCGTGGATCCTAATTATGTTACGTATAGCACGTTGATCCACGGTTATATCAAATCTGGAGAAATGCATGAGATACCAGAACTATACGAAGAAATGCATATACGTGGGCTTTTGCCAGTGTCTAATTTCAGAGGAAACATGAGTCCAACACCTGTAACTATAAAAACAAGGCAGATAAATAGTGCTGAACAATTAGATGTATCAATACATTCTGAAGGGTAGCTTCTTTGTTGGAAATTCTGCTCTAGATTGTTGATCTTTCATATTGCAACTCTTAAAGGCACTAAAACAATCCTTATCCTGCTTCATGCTGATTCGAAAGTCCAGATTACAATTTCAACAGGAACAATTTAGTAATTCTCCATAAAATTCACAATTATTTCATATTCTTCAAACATACTGATTTCATTCCATGAATTTATTAGGGTAACGTACACAATCATTATCAGTTTTATCCTGGTATCTTCTCCAAAGTCATTCACATTAGCTCACTTTACCTTTGTGGTTCAGGAGATCCACATTGACTTTGTGAAGATGCACATGCAACCACATTATGCTGGGTATTCTTGTTCTGAAACCATGAGGTACTTTACTGAGATTATCTTTACGTCATCATGGATTCATTTTATTCTTGTGCTATCTAGCATGGTACTCTAATTCTGTTTTATTATAGATTTATTTATTGGTAAAAATAATGCTGTGGATGACACCACCTGTGCATTTGTGGTTTAGGGGGAAAATTGATTCAATGTATTTGAATTTCATTATAAAAAAATTGACCAATTCTGTTGTTTTCTTTGTGGATCTTCCTTTAGAGGCTAGTGTAGTTTTCATCTTCACACACACAAAAATAGAGCAGACAGTTC',
 'description': 'NC_055986.1 Zingiber officinale cultivar Zhangliang chromosome 1B, Zo_v1.1, whole genome shotgun sequence',
 'start_pos': 0,
 'end_pos': 6200,
 }

Data Fields

• sequence: a string containing a DNA sequence from one of the 48 plant genomes
• description: a string indicating the species of the sequence as well as the NCBI id.
• 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 Plant Multi Species Genomes dataset has 3 splits: train, validation, and test.

Citation

@article{mendoza2023foundational,
  title={A Foundational Large Language Model for Edible Plant Genomes},
  author={Mendoza-Revilla, Javier and Trop, Evan and Gonzalez, Liam and Roller, Masa and Dalla-Torre, Hugo and de Almeida, Bernardo P and Richard, Guillaume and Caton, Jonathan and Lopez Carranza, Nicolas and Skwark, Marcin and others},
  journal={bioRxiv},
  pages={2023--10},
  year={2023},
  publisher={Cold Spring Harbor Laboratory}
}