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import argparse
import yaml
import scanpy as sc
from atac_preprocess import quality_control
from atac_preprocess import deepen_atac_data
from atac_preprocess import tfidf
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("--config_path", type=str, help="path to config file")
args = parser.parse_args()
with open(args.config_path, 'r') as file:
config = yaml.safe_load(file)
data_args = config["data_args"]
adata = sc.read_h5ad(data_args.get('atac_file_path'))
# adata.obs['celltype'] = adata.obs['Celltype_fig1']
if data_args.get("quality_control", False):
print(f"Before quality control: {adata.shape}")
adata = quality_control(
adata,
min_features=data_args.get("min_features"),
max_features=data_args.get("max_features"),
min_percent=data_args.get("min_percent"),
cell_type_col=data_args.get("cell_type_col", "cell type")
)
print(f"After quality control: {adata.shape}")
if data_args.get("tfidf", False):
print(f"Before tfidf: {adata.shape}")
adata.X = tfidf(adata.X) * 1e4
if data_args.get("deepen_atac", False):
adata = deepen_atac_data(adata, num_cell_merge=10)
print(f"After deepen: {adata.shape}")
if data_args.get("normalize", False):
sc.pp.normalize_total(adata)
if data_args.get("log_transform", False):
sc.pp.log1p(adata)
output_file_name = f"{data_args.get('atac_file_path')}".replace(".h5ad", "")
if data_args.get("quality_control", False):
output_file_name = f"{output_file_name}_quality_control"
if data_args.get("deepen_atac", False):
output_file_name = f"{output_file_name}_deepen"
if data_args.get("normalize", False):
output_file_name = f"{output_file_name}_normalized"
if data_args.get("log_transform", False):
output_file_name = f"{output_file_name}_log"
output_file_name = f"{output_file_name}.h5ad"
adata.write_h5ad(output_file_name)
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