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import pandas as pd
import os
from datasets import load_dataset
data_dir = os.path.join(os.getcwd(), "data")
species_list = ["human", "rat_SD", "mouse_BALB_c", "mouse_C57BL_6"]
for species in species_list:
species_url_file = os.path.join(os.getcwd(), species + "_oas_paired.txt")
with open(species_url_file, "r") as f:
for csv_file in f.readlines():
print(csv_file)
filename = os.path.basename(csv_file)
filename = os.path.splitext(filename)[0]
filename = os.path.splitext(filename)[0] # Not a typo, need to pull off the .gzip AND the .csv
df = pd.read_csv(
csv_file,
header=1,
compression="gzip",
on_bad_lines="warn",
)
df = df[
[
"sequence_id_heavy",
"sequence_heavy",
"locus_heavy",
"stop_codon_heavy",
"productive_heavy",
"rev_comp_heavy",
"sequence_alignment_aa_heavy",
"fwr1_aa_heavy",
"cdr1_aa_heavy",
"fwr2_aa_heavy",
"cdr2_aa_heavy",
"fwr3_aa_heavy",
"cdr3_aa_heavy",
"junction_aa_heavy",
"sequence_id_light",
"sequence_light",
"locus_light",
"stop_codon_light",
"productive_light",
"rev_comp_light",
"sequence_alignment_aa_light",
"fwr1_aa_light",
"cdr1_aa_light",
"fwr2_aa_light",
"cdr2_aa_light",
"fwr3_aa_light",
"cdr3_aa_light",
"junction_aa_light",
]
]
df.insert(0, "run", species)
output_path = os.path.join(data_dir, species)
if not os.path.exists(output_path):
os.makedirs(output_path, exist_ok=True)
df.to_parquet(
os.path.join(output_path, filename + ".parquet"), compression="gzip"
)
x = load_dataset(output_path)
print(x.num_rows)
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