macwiatrak/operon-identification-long-read-rna-sequencing-protein-sequences
Dataset for operon identification from long-read RNA sequencing A dataset of annotated operons across 5 distinct bacterial strains. The operons were annotated by running and analysing long-read RNA sequencing and identifying genes located on the same transcripts. The genome protein sequences have been extracted from GenBank. Each row contains whole bacterial genome represented by an ordered list of protein sequences. Usage For a complete example on how to read and… See the full description on the dataset page: https://huggingface.co/datasets/macwiatrak/operon-identification-long-read-rna-sequencing-protein-sequences.
Dataset for operon identification from long-read RNA sequencing
A dataset of annotated operons across 5 distinct bacterial strains. The operons were annotated by running and analysing long-read RNA sequencing and identifying genes located on the same transcripts.
The genome protein sequences have been extracted from GenBank. Each row contains whole bacterial genome represented by an ordered list of protein sequences.
Usage
For a complete example on how to read and use the dataset, see Bacformer zero-shot operon prediction tutorial.
from datasets import load_dataset
dataset = load_dataset("macwiatrak/operon-identification-long-read-rna-sequencing", split="test")
# select a strain, here we will go for Mycobacterium tuberculosis (mtb)
mtb = dataset[1]
# select operons on the chromosome, mtb has no plasmids so there is only one contig (i.e. chromosome)
contig_idx = 0
chrom_operons = mtb['operon_prot_indices'][contig_idx]
# select the first operon
operon_prot_indices = chrom_operons[0]
print(operon_prot_indices)
# get protein sequences of the proteins belonging to the operon
operon_prot_seqs = [mtb['protein_sequence'][contig_idx][idx] for idx in operon_prot_indices]
operon_locus_tags = [mtb['locus_tag'][contig_idx][idx] for idx in operon_prot_indices]See github repository for more details.