license: apache-2.0
tags:
- bacteria
- genomics
- prokaryotes
- gene_essentiality
- genes
- DNA
pretty_name: Dataset for predicting essential genes in bacterial genomes (DNA)
size_categories:
- n<1K
Dataset for essential genes prediction in bacterial genomes (DNA)
A dataset of 169,408 genes with gene essentiality labels (binary) from 51 bacterial genomes across 37 species.
The gene essentiality labels have been extracted from the Database of Essential Genes and the genome DNA sequences have been extracted from GenBank.
Each row contains whole bacterial genome together with annotated gene locations on the genome (start and end). We excluded duplicates and genomes with incomplete genomes.
Labels
The labels for each gene are provided in the dataset in the essential column.
Usage
We recommend loading the dataset in a streaming mode to prevent memory errors.
from datasets import load_dataset
ds = load_dataset("macwiatrak/bacbench-essential-genes-dna", split="validation")
# fetch an example
item = ds[0]
# get gene sequences
dna_seq = item['dna_seq']
gene_dna_seqs = [
item['dna_seq'][int(start - 1):int(end)] for start, end in zip(item["start"], item["end"])
]
# get labels
labels = item["essential"]
Split
We provide 60 / 20 /20 (%) train, validation and test splits respectively as part of the dataset. The split has been performed by randomly.
See github repository for details on how to embed the dataset with DNA and protein language models as well as code to predict gene essentiality. For coding sequence representation of the genome see the macwiatrak/bacbench-essential-genes-protein-sequences dataset.