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@@ -492,3 +492,15 @@ GSE274051/GSM8442682/spatial.h5ad filter=lfs diff=lfs merge=lfs -text
 GSE274051/GSM8442682/wsi.tif filter=lfs diff=lfs merge=lfs -text
 GSE274051/GSM8442683/spatial.h5ad filter=lfs diff=lfs merge=lfs -text
 GSE274051/GSM8442683/wsi.tif filter=lfs diff=lfs merge=lfs -text
+GSE274059/GSM8442776/spatial.h5ad filter=lfs diff=lfs merge=lfs -text
+GSE274059/GSM8442776/wsi.tif filter=lfs diff=lfs merge=lfs -text
+GSE274059/GSM8442777/spatial.h5ad filter=lfs diff=lfs merge=lfs -text
+GSE274059/GSM8442777/wsi.tif filter=lfs diff=lfs merge=lfs -text
+GSE274059/GSM8442778/spatial.h5ad filter=lfs diff=lfs merge=lfs -text
+GSE274059/GSM8442778/wsi.tif filter=lfs diff=lfs merge=lfs -text
+GSE274059/GSM8442779/spatial.h5ad filter=lfs diff=lfs merge=lfs -text
+GSE274059/GSM8442779/wsi.tif filter=lfs diff=lfs merge=lfs -text
+GSE274059/GSM8442780/spatial.h5ad filter=lfs diff=lfs merge=lfs -text
+GSE274059/GSM8442780/wsi.tif filter=lfs diff=lfs merge=lfs -text
+GSE274059/GSM8442781/spatial.h5ad filter=lfs diff=lfs merge=lfs -text
+GSE274059/GSM8442781/wsi.tif filter=lfs diff=lfs merge=lfs -text

GSE274059/.sentinel_report.json

@@ -0,0 +1,342 @@
+{
+  "gse_id": "GSE274059",
+  "scan_time": "2026-04-14T18:08:32",
+  "assets": [
+    {
+      "path": "GSE274059_RAW/GSM8442776_H-f_aligned_fiducials.jpg.gz",
+      "type": "File",
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+      "status": "OK",
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+      "mode": "RGB",
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+    },
+    {
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+      "type": "File",
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+      "status": "OK",
+      "category": "Image",
+      "shape": [
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+        2000
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+      "mode": "RGB",
+      "channels": 3,
+      "is_compressed": true
+    },
+    {
+      "path": "GSE274059_RAW/GSM8442776_H-f_tissue_lowres_image.png.gz",
+      "type": "File",
+      "file_size_mb": 0.29,
+      "status": "OK",
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+      "channels": 3,
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+    },
+    {
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+      "type": "File",
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+      "status": "OK",
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+      "channels": 3,
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+    },
+    {
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+      "channels": 3,
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+    },
+    {
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+    },
+    {
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+        2000
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+      "channels": 3,
+      "is_compressed": true
+    },
+    {
+      "path": "GSE274059_RAW/GSM8442776_H-f_detected_tissue_image.jpg.gz",
+      "type": "File",
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+      "status": "OK",
+      "category": "Image",
+      "shape": [
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+        2000
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+      "mode": "RGB",
+      "channels": 3,
+      "is_compressed": true
+    },
+    {
+      "path": "GSE274059_RAW/GSM8442781_L-d2_aligned_fiducials.jpg.gz",
+      "type": "File",
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+      "status": "OK",
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+      "shape": [
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+      "mode": "RGB",
+      "channels": 3,
+      "is_compressed": true
+    },
+    {
+      "path": "GSE274059_RAW/GSM8442780_L-d1_detected_tissue_image.jpg.gz",
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+      "status": "OK",
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+      "mode": "RGB",
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+    },
+    {
+      "path": "GSE274059_RAW/GSM8442779_L-f2_tissue_hires_image.png.gz",
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+      "is_compressed": true
+    },
+    {
+      "path": "GSE274059_RAW/GSM8442777_H-d_tissue_lowres_image.png.gz",
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+      "channels": 3,
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+    },
+    {
+      "path": "GSE274059_RAW/GSM8442777_H-d_tissue_hires_image.png.gz",
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+      "status": "OK",
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+      "shape": [
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+      "mode": "RGB",
+      "channels": 3,
+      "is_compressed": true
+    },
+    {
+      "path": "GSE274059_RAW/GSM8442781_L-d2_tissue_lowres_image.png.gz",
+      "type": "File",
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+      "status": "OK",
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+        600
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+      "channels": 3,
+      "is_compressed": true
+    },
+    {
+      "path": "GSE274059_RAW/GSM8442778_L-f1_detected_tissue_image.jpg.gz",
+      "type": "File",
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+      "status": "OK",
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+    {
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+    },
+    {
+      "path": "GSE274059_RAW/GSM8442779_L-f2_aligned_fiducials.jpg.gz",
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+    {
+      "path": "GSE274059_RAW/GSM8442781_L-d2_tissue_hires_image.png.gz",
+      "type": "File",
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+      "status": "OK",
+      "category": "Image",
+      "shape": [
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+        2000
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+      "mode": "RGB",
+      "channels": 3,
+      "is_compressed": true
+    },
+    {
+      "path": "GSE274059_RAW/GSM8442776_H-f_tissue_hires_image.png.gz",
+      "type": "File",
+      "file_size_mb": 3.04,
+      "status": "OK",
+      "category": "Image",
+      "shape": [
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+        2000
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+      "mode": "RGB",
+      "channels": 3,
+      "is_compressed": true
+    },
+    {
+      "path": "GSE274059_RAW/GSM8442780_L-d1_aligned_fiducials.jpg.gz",
+      "type": "File",
+      "file_size_mb": 1.01,
+      "status": "OK",
+      "category": "Image",
+      "shape": [
+        1855,
+        2000
+      ],
+      "mode": "RGB",
+      "channels": 3,
+      "is_compressed": true
+    },
+    {
+      "path": "GSE274059_RAW/GSM8442777_H-d_aligned_fiducials.jpg.gz",
+      "type": "File",
+      "file_size_mb": 1.07,
+      "status": "OK",
+      "category": "Image",
+      "shape": [
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+        2000
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+      "mode": "RGB",
+      "channels": 3,
+      "is_compressed": true
+    },
+    {
+      "path": "GSE274059_RAW/GSM8442777_H-d_detected_tissue_image.jpg.gz",
+      "type": "File",
+      "file_size_mb": 0.71,
+      "status": "OK",
+      "category": "Image",
+      "shape": [
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+    {
+      "path": "GSE274059_RAW/GSM8442778_L-f1_tissue_lowres_image.png.gz",
+      "type": "File",
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+      "status": "OK",
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+      "shape": [
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+      "mode": "RGB",
+      "channels": 3,
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+    },
+    {
+      "path": "GSE274059_RAW/GSM8442779_L-f2_detected_tissue_image.jpg.gz",
+      "type": "File",
+      "file_size_mb": 0.7,
+      "status": "OK",
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+      "mode": "RGB",
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+      "is_compressed": true
+    }
+  ]
+}

GSE274059/GSM8442776/.standardization_success

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GSE274059/GSM8442776/spatial.h5ad

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GSE274059/GSM8442777/.standardization_success

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GSE274059/GSM8442778/.standardization_success

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GSE274059/GSM8442779/.standardization_success

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GSE274059/GSM8442780/.standardization_success

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GSE274059/GSM8442781/.standardization_success

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GSE274059/GSM8442781/spatial.h5ad

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GSE274059/audit_report.json

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+{
+  "gse_id": "GSE274059",
+  "global_score": 100.0,
+  "threshold_limit": 0.03,
+  "summary": {
+    "total_samples": 6,
+    "passed_samples": 6,
+    "structural_fail_samples": 0,
+    "alignment_fail_samples": 0,
+    "error_samples": 0
+  },
+  "samples": [
+    {
+      "sample_id": "GSM8442780",
+      "status": "PASS",
+      "score": 100,
+      "spillover": 0.0,
+      "spot_count": 454,
+      "reason": null,
+      "weight": 0.1586303284416492
+    },
+    {
+      "sample_id": "GSM8442776",
+      "status": "PASS",
+      "score": 100,
+      "spillover": 0.0,
+      "spot_count": 369,
+      "reason": null,
+      "weight": 0.1289308176100629
+    },
+    {
+      "sample_id": "GSM8442781",
+      "status": "PASS",
+      "score": 100,
+      "spillover": 0.0,
+      "spot_count": 408,
+      "reason": null,
+      "weight": 0.14255765199161424
+    },
+    {
+      "sample_id": "GSM8442778",
+      "status": "PASS",
+      "score": 100,
+      "spillover": 0.0,
+      "spot_count": 662,
+      "reason": null,
+      "weight": 0.23130677847658979
+    },
+    {
+      "sample_id": "GSM8442779",
+      "status": "PASS",
+      "score": 100,
+      "spillover": 0.0,
+      "spot_count": 436,
+      "reason": null,
+      "weight": 0.15234102026554858
+    },
+    {
+      "sample_id": "GSM8442777",
+      "status": "PASS",
+      "score": 100,
+      "spillover": 0.0,
+      "spot_count": 533,
+      "reason": null,
+      "weight": 0.1862334032145353
+    }
+  ]
+}

GSE274059/standardize_GSE274059.py

@@ -0,0 +1,125 @@
+import os
+import sys
+import glob
+import json
+import gzip
+import io
+import shutil
+import pandas as pd
+import scanpy as sc
+import numpy as np
+from PIL import Image
+from concurrent.futures import ThreadPoolExecutor
+
+# Inject Expert Scripts Path
+sys.path.append("/cpfs01/projects-HDD/cfff-afe2df89e32e_HDD/jjh_19301050235/.agents/skills/ara-evolutionary-standardizer/scripts")
+import registry_utils
+
+GSE_ID = "GSE274059"
+INPUT_DIR = "/cpfs01/projects-HDD/cfff-afe2df89e32e_HDD/jjh_19301050235/my_data/preprint_data/Spatial-Clip/data/auto_standardize_react/data/2026_unzip_v4/GSE274059/GSE274059_RAW"
+OUTPUT_DIR = "/cpfs01/projects-HDD/cfff-afe2df89e32e_HDD/jjh_19301050235/my_data/preprint_data/Spatial-Clip/data/auto_standardize_react/data/2026_standardized/GSE274059"
+
+def process_gsm(gsm_id, files):
+    try:
+        sample_name = gsm_id
+        target_path = os.path.join(OUTPUT_DIR, sample_name)
+        os.makedirs(target_path, exist_ok=True)
+
+        # 1. Load Matrix (Handling .h5.gz)
+        h5_path = files.get('matrix_h5')
+        if not h5_path:
+            return f"{gsm_id}: Missing H5"
+            
+        if h5_path.endswith('.gz'):
+            temp_h5 = os.path.join(target_path, "temp_matrix.h5")
+            with gzip.open(h5_path, 'rb') as f_in:
+                with open(temp_h5, 'wb') as f_out:
+                    shutil.copyfileobj(f_in, f_out)
+            adata = sc.read_10x_h5(temp_h5)
+            os.remove(temp_h5)
+        else:
+            adata = sc.read_10x_h5(h5_path)
+            
+        adata.var_names_make_unique()
+
+        # 2. Load Coordinates
+        pos_path = files.get('positions')
+        if pos_path.endswith('.gz'):
+            with gzip.open(pos_path, 'rt') as f:
+                pos_df = pd.read_csv(f, header=None, index_col=0)
+        else:
+            pos_df = pd.read_csv(pos_path, header=None, index_col=0)
+            
+        pos_df.columns = ["in_tissue", "array_row", "array_col", "pxl_row_in_fullres", "pxl_col_in_fullres"]
+        
+        # 3. Load Scaling
+        scaling_path = files.get('scalefactors')
+        with (gzip.open(scaling_path, 'rt') if scaling_path.endswith('.gz') else open(scaling_path, 'r')) as f:
+            scalefactors = json.load(f)
+        
+        # 4. Load Image
+        img_path = files.get('hires_image')
+        if img_path.endswith('.gz'):
+            with gzip.open(img_path, 'rb') as f:
+                img_data = f.read()
+                img = Image.open(io.BytesIO(img_data))
+        else:
+            img = Image.open(img_path)
+        img.save(os.path.join(target_path, "wsi.tif"))
+        
+        # 5. Align Coordinates
+        scale = scalefactors['tissue_hires_scalef']
+        common_barcodes = adata.obs_names.intersection(pos_df.index)
+        adata = adata[common_barcodes].copy()
+        pos_df = pos_df.loc[common_barcodes]
+        
+        adata.obs['x'] = pos_df['pxl_col_in_fullres'].astype(float) * scale
+        adata.obs['y'] = pos_df['pxl_row_in_fullres'].astype(float) * scale
+        adata.obs['pxl_col_in_fullres'] = adata.obs['x']
+        adata.obs['pxl_row_in_fullres'] = adata.obs['y']
+        
+        # 6. Metadata
+        adata.uns['organism'] = "mouse"
+        adata.uns['tissue'] = "hippocampus"
+        adata.uns['disease'] = "High-fat diet (HFD)"
+        adata.uns['sex'] = "Not Reported (Verified by Source)"
+        adata.uns['age'] = "Not Reported (Verified by Source)"
+        adata.uns['technology'] = "10X Visium"
+        adata.uns['stain_type'] = "H&E"
+        adata.uns['publication_doi'] = "10.1101/2024.08.02.606339"
+        adata.uns['repository_id'] = f"GEO:{GSE_ID}"
+        
+        adata.write_h5ad(os.path.join(target_path, "spatial.h5ad"))
+        with open(os.path.join(target_path, ".standardization_success"), "w") as f:
+            f.write("Success")
+            
+        return f"{gsm_id}: Success"
+    except Exception as e:
+        import traceback
+        traceback.print_exc()
+        return f"{gsm_id}: Failed - {str(e)}"
+
+def run():
+    gsm_map = {}
+    for f in os.listdir(INPUT_DIR):
+        if f.startswith("GSM"):
+            gsm_id = f.split("_")[0]
+            if gsm_id not in gsm_map:
+                gsm_map[gsm_id] = {}
+            
+            if f.endswith(".h5") or f.endswith(".h5.gz"): gsm_map[gsm_id]['matrix_h5'] = os.path.join(INPUT_DIR, f)
+            if "positions" in f: gsm_map[gsm_id]['positions'] = os.path.join(INPUT_DIR, f)
+            if "scalefactors" in f: gsm_map[gsm_id]['scalefactors'] = os.path.join(INPUT_DIR, f)
+            if "hires_image" in f: gsm_map[gsm_id]['hires_image'] = os.path.join(INPUT_DIR, f)
+
+    with ThreadPoolExecutor(max_workers=128) as executor:
+        results = list(executor.map(lambda g: process_gsm(g, gsm_map[g]), gsm_map))
+    
+    for r in results:
+        print(r)
+    
+    status = "success" if any("Success" in r for r in results) else "failed"
+    registry_utils.update_gse_registry(GSE_ID, status)
+
+if __name__ == "__main__":
+    run()

GSE274059/tree_scan.txt

@@ -0,0 +1,68 @@
+
+[TREE SCAN] /cpfs01/projects-HDD/cfff-afe2df89e32e_HDD/jjh_19301050235/my_data/preprint_data/Spatial-Clip/data/auto_standardize_react/data/2026_unzip_v4/GSE274059
+--------------------------------------------------
+├── GSE274059_RAW
+  ├── .extraction_success
+  ├── GSM8442776_H-f_aligned_fiducials.jpg.gz
+  ├── GSM8442776_H-f_barcodes.tsv.gz [CELL_BARCODES]
+  ├── GSM8442776_H-f_detected_tissue_image.jpg.gz
+  ├── GSM8442776_H-f_features.tsv.gz [GENE_FEATURES]
+  ├── GSM8442776_H-f_filtered_feature_bc_matrix.h5.gz
+  ├── GSM8442776_H-f_matrix.mtx.gz [RAW_MATRIX]
+  ├── GSM8442776_H-f_scalefactors_json.json.gz
+  ├── GSM8442776_H-f_tissue_hires_image.png.gz
+  ├── GSM8442776_H-f_tissue_lowres_image.png.gz
+  ├── GSM8442776_H-f_tissue_positions.csv.gz
+  ├── GSM8442777_H-d_aligned_fiducials.jpg.gz
+  ├── GSM8442777_H-d_barcodes.tsv.gz [CELL_BARCODES]
+  ├── GSM8442777_H-d_detected_tissue_image.jpg.gz
+  ├── GSM8442777_H-d_features.tsv.gz [GENE_FEATURES]
+  ├── GSM8442777_H-d_filtered_feature_bc_matrix.h5.gz
+  ├── GSM8442777_H-d_matrix.mtx.gz [RAW_MATRIX]
+  ├── GSM8442777_H-d_scalefactors_json.json.gz
+  ├── GSM8442777_H-d_tissue_hires_image.png.gz
+  ├── GSM8442777_H-d_tissue_lowres_image.png.gz
+  ├── GSM8442777_H-d_tissue_positions.csv.gz
+  ├── GSM8442778_L-f1_aligned_fiducials.jpg.gz
+  ├── GSM8442778_L-f1_barcodes.tsv.gz [CELL_BARCODES]
+  ├── GSM8442778_L-f1_detected_tissue_image.jpg.gz
+  ├── GSM8442778_L-f1_features.tsv.gz [GENE_FEATURES]
+  ├── GSM8442778_L-f1_filtered_feature_bc_matrix.h5.gz
+  ├── GSM8442778_L-f1_matrix.mtx.gz [RAW_MATRIX]
+  ├── GSM8442778_L-f1_scalefactors_json.json.gz
+  ├── GSM8442778_L-f1_tissue_hires_image.png.gz
+  ├── GSM8442778_L-f1_tissue_lowres_image.png.gz
+  ├── GSM8442778_L-f1_tissue_positions.csv.gz
+  ├── GSM8442779_L-f2_aligned_fiducials.jpg.gz
+  ├── GSM8442779_L-f2_barcodes.tsv.gz [CELL_BARCODES]
+  ├── GSM8442779_L-f2_detected_tissue_image.jpg.gz
+  ├── GSM8442779_L-f2_features.tsv.gz [GENE_FEATURES]
+  ├── GSM8442779_L-f2_filtered_feature_bc_matrix.h5.gz
+  ├── GSM8442779_L-f2_matrix.mtx.gz [RAW_MATRIX]
+  ├── GSM8442779_L-f2_scalefactors_json.json.gz
+  ├── GSM8442779_L-f2_tissue_hires_image.png.gz
+  ├── GSM8442779_L-f2_tissue_lowres_image.png.gz
+  ├── GSM8442779_L-f2_tissue_positions.csv.gz
+  ├── GSM8442780_L-d1_aligned_fiducials.jpg.gz
+  ├── GSM8442780_L-d1_barcodes.tsv.gz [CELL_BARCODES]
+  ├── GSM8442780_L-d1_detected_tissue_image.jpg.gz
+  ├── GSM8442780_L-d1_features.tsv.gz [GENE_FEATURES]
+  ├── GSM8442780_L-d1_filtered_feature_bc_matrix.h5.gz
+  ├── GSM8442780_L-d1_matrix.mtx.gz [RAW_MATRIX]
+  ├── GSM8442780_L-d1_scalefactors_json.json.gz
+  ├── GSM8442780_L-d1_tissue_hires_image.png.gz
+  ├── GSM8442780_L-d1_tissue_lowres_image.png.gz
+  ├── GSM8442780_L-d1_tissue_positions.csv.gz
+  ├── GSM8442781_L-d2_aligned_fiducials.jpg.gz
+  ├── GSM8442781_L-d2_barcodes.tsv.gz [CELL_BARCODES]
+  ├── GSM8442781_L-d2_detected_tissue_image.jpg.gz
+  ├── GSM8442781_L-d2_features.tsv.gz [GENE_FEATURES]
+  ├── GSM8442781_L-d2_filtered_feature_bc_matrix.h5.gz
+  ├── GSM8442781_L-d2_matrix.mtx.gz [RAW_MATRIX]
+  ├── GSM8442781_L-d2_scalefactors_json.json.gz
+  ├── GSM8442781_L-d2_tissue_hires_image.png.gz
+  ├── GSM8442781_L-d2_tissue_lowres_image.png.gz
+  ├── GSM8442781_L-d2_tissue_positions.csv.gz
+├── aria2_tasks.txt
+├── filelist.txt
+├── robots.txt