metadata
pretty_name: BFD Source Archive Index
license: other
tags:
- biology
- protein
- sequence-database
- bfd
- fasta
- archive
- parquet
configs:
- config_name: default
data_files:
- split: train
path: data/train-*.parquet
- split: test
path: data/test-*.parquet
BFD Source Archive Index
BFD is a very large clustered protein sequence database built from UniProt and metagenomic sequence resources, commonly used for homology search and multiple sequence alignment generation.
Splits
The split is deterministic by chunk identifier: sha256(index_id) % 10. Bucket 0 is test; buckets 1 through 9 are train.
| Split | Rows |
|---|---|
| train | 255 |
| test | 17 |
| total | 272 |
Source File
| File | Size |
|---|---|
bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt.tar.gz |
291,649,557,441 bytes |
Usage
pip install datasets
Load the archive index:
from datasets import load_dataset
ds = load_dataset("LiteFold/BFD")
print(ds)
print(ds["train"][0])
Load one split:
from datasets import load_dataset
train = load_dataset("LiteFold/BFD", split="train")
test = load_dataset("LiteFold/BFD", split="test")
Download the original archive:
from huggingface_hub import hf_hub_download
archive_path = hf_hub_download(
repo_id="LiteFold/BFD",
repo_type="dataset",
filename="bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt.tar.gz",
)
Load the source-file manifest:
import pandas as pd
from huggingface_hub import hf_hub_download
path = hf_hub_download(
repo_id="LiteFold/BFD",
repo_type="dataset",
filename="metadata/source_files.parquet",
)
source_files = pd.read_parquet(path)
print(source_files)
Columns
| Column | Description |
|---|---|
index_id |
Stable row ID for one compressed chunk. |
repo_id |
Hugging Face dataset repository. |
source_file |
Source archive filename. |
source_sha |
Source repository commit used to build the index. |
source_format |
Source archive format. |
chunk_index |
Zero-based compressed chunk index. |
byte_start |
Inclusive compressed byte offset. |
byte_end_exclusive |
Exclusive compressed byte offset. |
chunk_size_bytes |
Compressed chunk size in bytes. |
total_size_bytes |
Full compressed archive size. |
chunk_size_gib |
Target chunk size in GiB. |
is_first_chunk |
Whether the row indexes the first chunk. |
is_last_chunk |
Whether the row indexes the final chunk. |
access_note |
Note describing the index scope. |
split_bucket |
Deterministic split bucket from sha256(index_id) % 10. |
Citation
@article{steinegger2019bfd,
title = {Protein-level assembly increases protein sequence recovery from metagenomic samples manyfold},
author = {Steinegger, Martin and Mirdita, Milot and S{\"o}ding, Johannes},
journal = {Nature Methods},
volume = {16},
pages = {603--606},
year = {2019},
doi = {10.1038/s41592-019-0437-4}
}