Datasets:
File size: 1,997 Bytes
bb8455b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 | import pandas as pd
from pathlib import Path
import re
# Input
tsv_path = "sabdab_summary_all_sorted.tsv"
base_dir = Path("sabdab_dataset")
df = pd.read_csv(tsv_path, sep="\t")
def find_file(directory, pattern):
if not directory.exists():
return None
regex = re.compile(pattern, re.IGNORECASE)
for f in directory.iterdir():
if f.is_file() and regex.fullmatch(f.name):
# return actual existing path relative to sabdab_dataset
return str(f.relative_to(base_dir.parent))
return None
def get_paths(row):
pdb = str(row["pdb"])
H = str(row["Hchain"])
L = str(row["Lchain"])
pdb_dir = base_dir / pdb.lower()
return pd.Series({
"abangle": find_file(
pdb_dir / "abangle",
rf"{pdb}\.abangle"
),
"annotation_H": find_file(
pdb_dir / "annotation",
rf"{pdb}_{H}_VH\.ann"
),
"annotation_L": find_file(
pdb_dir / "annotation",
rf"{pdb}_{L}_VL\.ann"
),
"imgt_H": find_file(
pdb_dir / "imgt",
rf"{pdb}_{H}_H\.ann"
),
"imgt_L": find_file(
pdb_dir / "imgt",
rf"{pdb}_{L}_L\.ann"
),
"sequence_raw": find_file(
pdb_dir / "sequence",
rf"{pdb}_raw\.pdb"
),
"sequence_H": find_file(
pdb_dir / "sequence",
rf"{pdb}_{H}_VH\.fa"
),
"sequence_L": find_file(
pdb_dir / "sequence",
rf"{pdb}_{L}_VL\.fa"
),
"structure": find_file(
pdb_dir / "structure",
rf"{pdb}\.pdb"
),
"structure_chothia": find_file(
pdb_dir / "structure" / "chothia",
rf"{pdb}\.pdb"
),
})
# Apply row-wise
new_cols = df.apply(get_paths, axis=1)
df = pd.concat([df, new_cols], axis=1)
df.to_csv("sabdab_summary_all_with_paths.tsv", sep="\t", index=False) |