Datasets:
File size: 1,989 Bytes
d3f6b75 | 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 | import pandas as pd
import numpy as np
# This was downloaded from https://github.com/tommyhuangthu/SAAINT/tree/main/saaintdb
saaint_db = pd.read_csv('saaintdb_20260226_all.csv')
# Add 'PDB_ID_chain' column (will be used as unique ID)
# Add 'hl_label' column (HL, H_only, L_only)
def chain_ok(x):
# Check if chain ID is valid (not NaN and not "N.A.")
if pd.isna(x):
return False
x = str(x).strip()
return (x != "") and (x.upper() not in {"N.A."})
def hl_label_from_row(row):
# Determine HL status label for each row
h_ok = chain_ok(row["H_chain_ID"])
l_ok = chain_ok(row["L_chain_ID"])
if h_ok and l_ok:
return "HL"
elif h_ok and (not l_ok):
return "H_only"
elif (not h_ok) and l_ok:
return "L_only"
else:
return "none"
def make_unique_id(row):
# Create a unique identifier based on PDB ID and chain IDs
pdb_id = str(row["PDB_ID"]).strip()
heavy = str(row["H_chain_ID"]).strip() if not pd.isna(row["H_chain_ID"]) else ""
light = str(row["L_chain_ID"]).strip() if not pd.isna(row["L_chain_ID"]) else ""
h_ok = chain_ok(heavy)
l_ok = chain_ok(light)
if h_ok and l_ok:
return f"{pdb_id}_{heavy}_{light}"
elif h_ok:
return f"{pdb_id}_{heavy}"
elif l_ok:
return f"{pdb_id}_{light}"
else:
return pdb_id
# 1) Generate unique IDs for each antibody chain combination
saaint_db["PDB_ID_chain"] = saaint_db.apply(make_unique_id, axis=1)
# 2) Generate HL status label (strata) for each row
saaint_db["hl_label"] = saaint_db.apply(hl_label_from_row, axis=1)
# 3) Create a PDB-level summary (remove duplicates caused by multiple rows per PDB)
pdb_summary = (
saaint_db[["PDB_ID", "hl_label"]]
.drop_duplicates(subset=["PDB_ID"])
.copy()
)
# 4) Print the number of unique PDB entries per HL label
print("=== Number of unique PDBs per hl_label ===")
print(pdb_summary["hl_label"].value_counts(dropna=False).to_string())
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