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import pandas as pd
import datasets
_DESCRIPTION = """\
Multi-source dataset of antibody-mutation interactions including IC50, binding, escape, and affinity measurements.
"""
_FEATURES = {
'antibody_name': datasets.Value("string"),
'antigen_lineage': datasets.Value("string"),
'target_value': datasets.Value("float"),
'target_type': datasets.Value("string"),
'source_name': datasets.Value("string"),
'source_doi': datasets.Value("string"),
'assay_name': datasets.Value("string"),
'pdb_id': datasets.Value("string"),
'structure_release_date': datasets.Value("string"),
'structure_resolution': datasets.Value("float"),
'mutations': datasets.Value("string"),
'antigen_chain_ids': datasets.Value("string"),
'antigen_domain': datasets.Value("string"),
'antigen_residue_indices': datasets.Value("string"),
'antigen_residue_indices_trimmed': datasets.Value("string"),
'antigen_host': datasets.Value("string"),
'antibody_heavy_chain_id': datasets.Value("string"),
'antibody_light_chain_id': datasets.Value("string"),
'epitope_residues': datasets.Value("string"),
'epitope_mutations': datasets.Value("string"),
'epitope_domain': datasets.Value("string"),
'epitope_alteration_count': datasets.Value("string"),
'spike_sequence': datasets.Value("string"),
'antibody_heavy_chain_sequence': datasets.Value("string"),
'antibody_light_chain_sequence': datasets.Value("string"),
'antibody_vh_sequence': datasets.Value("string"),
'antibody_vl_sequence': datasets.Value("string"),
'antigen_sequence': datasets.Value("string"),
'antigen_sequence_trimmed': datasets.Value("string"),
'antigen_sequence_without_indels': datasets.Value("string"),
'antigen_sequence_trimmed_without_indels': datasets.Value("string"),
'antigen_pdb_sequence': datasets.Value("string"),
'antigen_pdb_sequence_trimmed': datasets.Value("string"),
}
_TABLES = {
"drdb": {
"file": "data/drdb_binding_potency.parquet",
"features": {
**_FEATURES,
}
},
"covabdab": {
"file": "data/covabdab_binding.parquet",
"features": {
**{
**_FEATURES,
"target_value": datasets.Value("bool"),
}
}
},
"dms_bloom": {
"file": "data/dms_bloom_ab_escape.parquet",
"features": {
**_FEATURES,
}
},
"dms_cao": {
"file": "data/dms_cao_ab_escape.parquet",
"features": {
**_FEATURES,
}
},
"jian_elisa": {
"file": "data/jian_elisa_ab_ic50.parquet",
"features": {
**_FEATURES,
}
},
"spr": {
"file": "data/spr_ab_affinity.parquet",
"features": {
**_FEATURES,
}
}
}
class CovUniBindConfig(datasets.BuilderConfig):
def __init__(self, **kwargs):
super().__init__(version=datasets.Version("1.0.0"), **kwargs)
class CovUniBind(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
CovUniBindConfig(name=table, description=f"{table} subset") for table in _TABLES
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(_TABLES[self.config.name]["features"]),
)
def _split_generators(self, dl_manager):
file_path = _TABLES[self.config.name]["file"]
data_path = dl_manager.download_and_extract(file_path)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_path}),
]
def _generate_examples(self, filepath):
df = pd.read_parquet(filepath)
for idx, row in df.iterrows():
yield idx, row.to_dict()
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