Datasets:

bloyal
/

oas-paired-sequence-data

	# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	# See the License for the specific language governing permissions and
	# limitations under the License.
	# TODO: Address all TODOs and remove all explanatory comments
	"""Paired sequences from the Observed Antibody Space database"""


	import csv
	import json
	import os

	import datasets

	_CITATION = """\
	@article{Olsen_Boyles_Deane_2022,
	title={Observed Antibody Space: A diverse database of cleaned, annotated, and translated unpaired and paired antibody sequences},
	volume={31}, rights={© 2021 The Authors. Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.},
	ISSN={1469-896X}, DOI={10.1002/pro.4205},
	number={1}, journal={Protein Science}, author={Olsen, Tobias H. and Boyles, Fergus and Deane, Charlotte M.},
	year={2022}, pages={141–146}, language={en} }

	"""
	_DESCRIPTION = """\
	Paired heavy and light chain antibody sequences for multiple species.
	"""

	_HOMEPAGE = "https://opig.stats.ox.ac.uk/webapps/oas/"

	_LICENSE = "cc-by-4.0"

	_URL = "https://aws-hcls-ml.s3.amazonaws.com/oas-paired-sequence-data/"

	_URLS = {
	"human": _URL + "human.zip",
	"rat_SD": _URL + "rat_SD.zip",
	"mouse_BALB_c": _URL + "mouse_BALB_c.zip",
	"mouse_C57BL_6": _URL + "mouse_C57BL_6.zip",
	}

	_FEATURES = datasets.Features(
	{
	"sequence_id_heavy": datasets.Value("string"),
	"sequence_heavy": datasets.Value("string"),
	"locus_heavy": datasets.Value("string"),
	"stop_codon_heavy": datasets.Value("string"),
	"productive_heavy": datasets.Value("string"),
	"rev_comp_heavy": datasets.Value("string"),
	"sequence_alignment_aa_heavy": datasets.Value("string"),
	"fwr1_aa_heavy": datasets.Value("string"),
	"cdr1_aa_heavy": datasets.Value("string"),
	"fwr2_aa_heavy": datasets.Value("string"),
	"cdr2_aa_heavy": datasets.Value("string"),
	"fwr3_aa_heavy": datasets.Value("string"),
	"cdr3_aa_heavy": datasets.Value("string"),
	"junction_aa_heavy": datasets.Value("string"),
	"sequence_id_light": datasets.Value("string"),
	"sequence_light": datasets.Value("string"),
	"locus_light": datasets.Value("string"),
	"stop_codon_light": datasets.Value("string"),
	"productive_light": datasets.Value("string"),
	"rev_comp_light": datasets.Value("string"),
	"sequence_alignment_aa_light": datasets.Value("string"),
	"fwr1_aa_light": datasets.Value("string"),
	"cdr1_aa_light": datasets.Value("string"),
	"fwr2_aa_light": datasets.Value("string"),
	"cdr2_aa_light": datasets.Value("string"),
	"fwr3_aa_light": datasets.Value("string"),
	"cdr3_aa_light": datasets.Value("string"),
	"junction_aa_light": datasets.Value("string"),
	}
	)

	class OasPairedSequenceData(datasets.GeneratorBasedBuilder):
	"""OAS paired sequence data."""

	VERSION = datasets.Version("1.1.0")

	# You will be able to load one or the other configurations in the following list with
	# data = datasets.load_dataset('my_dataset', 'first_domain')
	# data = datasets.load_dataset('my_dataset', 'second_domain')
	BUILDER_CONFIGS = [
	datasets.BuilderConfig(name="human", version=VERSION, description="Human"),
	datasets.BuilderConfig(name="rat_SD", version=VERSION, description="rat_SD"),
	datasets.BuilderConfig(
	name="mouse_BALB_c", version=VERSION, description="mouse_BALB_c"
	),
	datasets.BuilderConfig(
	name="mouse_C57BL_6", version=VERSION, description="mouse_C57BL_6"
	),
	]

	def _info(self):

	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=_FEATURES,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	# TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
	# If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name

	# dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
	# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
	# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
	urls = _URLS[self.config.name]
	data_dir = dl_manager.download_and_extract(urls)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={
	# "filepath": os.path.join(data_dir, "train.jsonl"),
	"filepath": data_dir,
	"split": "train",
	},
	),
	# datasets.SplitGenerator(
	# name=datasets.Split.VALIDATION,
	# # These kwargs will be passed to _generate_examples
	# gen_kwargs={
	# "filepath": os.path.join(data_dir, "dev.jsonl"),
	# "split": "dev",
	# },
	# ),
	# datasets.SplitGenerator(
	# name=datasets.Split.TEST,
	# # These kwargs will be passed to _generate_examples
	# gen_kwargs={
	# "filepath": os.path.join(data_dir, "test.jsonl"),
	# "split": "test",
	# },
	# ),
	]

	# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
	def _generate_examples(self, filepath, split):
	# TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
	# The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
	with open(filepath, encoding="utf-8") as f:
	for key, row in enumerate(f):
	data = json.loads(row)
	yield key, data
	# yield key, {
	# "sentence": data["sentence"],
	# "option2": data["option2"],
	# "second_domain_answer": ""
	# }