update parquet

README.md

@@ -23,6 +23,6 @@ configs:
 - https://opig.stats.ox.ac.uk/webapps/oas/oas_paired/
 
 
-### Dataset Summary
+## Dataset Summary
 
 Paired heavy- and light-chain sequence information from the Observed Antibody Space (OAS) database, downloaded on September 9, 2023.

human.parquet

@@ -1,3 +1,3 @@
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-oid sha256:15f68167648ede70b384eb9671c162617a251bf47ce758702ce6912c2cbfe05b
-size 60616532
+oid sha256:385678cd991b8639196d97b51f1f2396d32ced223bdacd60ffb806cf3b568701
+size 92818695

mouse_BALB_c.parquet

@@ -1,3 +1,3 @@
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-oid sha256:2e0991362b6f59e1fec7751d2696db0d4ef4ab6c609a9d87d98c8ec6061df705
-size 319404
+oid sha256:aadc6d7524d60d80109143772bc307bae06b8aabace45c87bdd2ca3aa7dd777f
+size 586744

mouse_C57BL_6.parquet

@@ -1,3 +1,3 @@
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-oid sha256:33b0a43b2d4bcc9e24d6d1f5c747dbc9a21b4e46220da6786f0fda6e024b6f35
-size 90331
+oid sha256:f46d6e00e6bde03b91675d2ba03dcb3c6f67c944ae8dd9606a6c373a07c61ae3
+size 174681

rat_SD.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1dd3a2a45f22e9e87cc13891f2db9c9e74129c23b7e8b94eda81fa1423863c40
-size 1082597
+oid sha256:5b60b14ea7fe3c0216f8640b6cacd1e63543e15663e308d6998a8c6a0eac87e8
+size 2053567

src/download_and_process_data.py

@@ -9,9 +9,7 @@ species_list = ["human", "rat_SD", "mouse_BALB_c", "mouse_C57BL_6"]
 
 for species in species_list:
     print(f"Downloading {species} files")
-    species_df = pd.DataFrame(
-        columns=["run_id", "sequence_alignment_aa_heavy", "sequence_alignment_aa_light"]
-    )
+    list_of_df = []
     species_url_file = os.path.join(data_dir, species + "_oas_paired.txt")
     with open(species_url_file, "r") as f:
         for csv_file in f.readlines():
@@ -27,15 +25,24 @@ for species in species_list:
             run_data = run_data[
                 [
                     "sequence_alignment_aa_heavy",
+                    "cdr1_aa_heavy",
+                    "cdr2_aa_heavy",
+                    "cdr3_aa_heavy",
                     "sequence_alignment_aa_light",
+                    "cdr1_aa_light",
+                    "cdr2_aa_light",
+                    "cdr3_aa_light",
                 ]
             ]
-            run_data.insert(0, "run_id", run_id)
-            species_df = pd.concat([species_df, run_data])
+            run_data.insert(
+                0, "pair_id", run_id + "_" + run_data.reset_index().index.map(str)
+            )
+            list_of_df.append(run_data)
+        species_df = pd.concat(list_of_df, ignore_index=True)
         print(f"{species} output summary:")
         print(species_df.head())
         print(species_df.shape)
         output_file_name = os.path.join(output_path, species + ".parquet")
         print(f"Creating {output_file_name}")
-        species_df.to_parquet(output_file_name, compression="gzip")
+        species_df.to_parquet(output_file_name, compression="gzip", index=False)
 

src/oas-paired-sequence-data.py

@@ -1,162 +0,0 @@
-# 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": ""
-                # }
-