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b282437 | 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 | import anndata as ad
import pandas as pd
import os
import glob
h5ad_dir = "C:/Users/Swamy/OneDrive - Zafrens/Desktop/Z-Screen Deepdive/Shared_Source_Data_June2026/external_reference/scperturb_downloads"
files = glob.glob(os.path.join(h5ad_dir, "*.h5ad"))
metadata_records = []
for f in files:
try:
adata = ad.read_h5ad(f, backed='r')
dataset_name = os.path.basename(f)
# extract metadata safely
cell_lines = adata.obs['cell_line'].unique().tolist() if 'cell_line' in adata.obs else []
perturbations = adata.obs['perturbation'].unique().tolist() if 'perturbation' in adata.obs else []
n_cells = adata.n_obs
n_vars = adata.n_vars
metadata_records.append({
"dataset_id": dataset_name.replace(".h5ad", ""),
"file": dataset_name,
"cell_lines": ", ".join([str(x) for x in cell_lines]),
"num_perturbations": len(perturbations),
"num_cells": n_cells,
"num_genes": n_vars
})
print(f"Processed {dataset_name}")
except Exception as e:
print(f"Error reading {f}: {e}")
if metadata_records:
df = pd.DataFrame(metadata_records)
out_csv = os.path.join(h5ad_dir, "scperturb_summary_metadata.csv")
df.to_csv(out_csv, index=False)
print(f"\nMetadata successfully extracted to {out_csv}")
print(df)
else:
print("No complete metadata could be extracted yet.")
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