diff --git a/examples/herc2/classify_herc2.py b/examples/herc2/classify_herc2.py
index fc5112d..393aae1 100644
--- a/examples/herc2/classify_herc2.py
+++ b/examples/herc2/classify_herc2.py
@@ -10,6 +10,15 @@
 # (A;G) also tends toward brown.
 # (G;G) gives blue eye color ~99% of the time.
 
+def _format_allele_label(allele):
+    if isinstance(allele, Alleles):
+        return ",".join(sorted(a.value for a in allele))
+    if isinstance(allele, str):
+        return allele
+    if hasattr(allele, "__iter__"):
+        return ",".join(sorted(str(a) for a in allele))
+    return str(allele)
+
 class HERC2Classifier(GenotypeClassifier):
     def classify(self, matches):
         match = matches.get(rs12913832)
@@ -25,10 +34,14 @@ def classify(self, matches):
             result = "No call"
             genotype_sorted = None
             match_type = MatchType.NO_CALL.value
+            ref_count = 0
+            alt_count = 0
         else:
             genotype_sorted = match.genotype_sorted
             result = eye_color_map.get(genotype_sorted, "Unknown")
             match_type = match.match_type.value
+            ref_count = match.ref_count
+            alt_count = match.alt_count
         
         # Extract properties from match (source_row has the actual data from the file)
         if match and match.source_row:
@@ -41,15 +54,21 @@ def classify(self, matches):
             position = None
         
         # Create report row using match properties
+        ref_label = _format_allele_label(rs12913832.ref)
+        alt_label = _format_allele_label(rs12913832.alt)
         report_row = {
             "participant_id": self.participant_id,
             "filename": self.filename,
             "rsid": rsid,
             "chromosome": chromosome,
             "position": position,
+            "ref": ref_label,
+            "alt": alt_label,
             "genotype": genotype_sorted,
             "match_type": match_type,
             "eye_color": result,
+            "ref_count": ref_count,
+            "alt_count": alt_count,
         }
         
         # Write to TSV file (as a list with one row)
@@ -93,6 +112,8 @@ def test_brown_homozygous():
     assert result[0]["rsid"] == "rs12913832"
     assert result[0]["chromosome"] == "15"
     assert result[0]["position"] == 28120472
+    assert result[0]["ref_count"] == 2
+    assert result[0]["alt_count"] == 0
     # Cleanup
     os.remove("result_HERC2_TEST_ID.tsv")
 
@@ -104,6 +125,8 @@ def test_brown_heterozygous_unsorted():
     assert result[0]["match_type"] == MatchType.VARIANT_CALL.value
     assert result[0]["participant_id"] == "TEST_ID"
     assert result[0]["filename"] == "test.txt"
+    assert result[0]["ref_count"] == 1
+    assert result[0]["alt_count"] == 1
     # Cleanup
     os.remove("result_HERC2_TEST_ID.tsv")
 
@@ -115,6 +138,8 @@ def test_blue_homozygous():
     assert result[0]["match_type"] == MatchType.VARIANT_CALL.value
     assert result[0]["participant_id"] == "TEST_ID"
     assert result[0]["filename"] == "test.txt"
+    assert result[0]["ref_count"] == 0
+    assert result[0]["alt_count"] == 2
     # Cleanup
     os.remove("result_HERC2_TEST_ID.tsv")
 
@@ -126,11 +151,13 @@ def test_no_call():
     assert result[0]["match_type"] == MatchType.NO_CALL.value
     assert result[0]["participant_id"] == "TEST_ID"
     assert result[0]["filename"] == "test.txt"
+    assert result[0]["ref_count"] == 0
+    assert result[0]["alt_count"] == 0
     # Cleanup
     os.remove("result_HERC2_TEST_ID.tsv")
 
 def test_unexpected_allele_c():
-    """Test handling of unexpected C allele (not in reference map)."""
+    'Test handling of unexpected C allele (not in reference map).'
     result = classify_fixture("AC")
     assert len(result) == 1
     assert result[0]["eye_color"] == "Unknown"
@@ -138,5 +165,7 @@ def test_unexpected_allele_c():
     assert result[0]["match_type"] == MatchType.VARIANT_CALL.value
     assert result[0]["participant_id"] == "TEST_ID"
     assert result[0]["filename"] == "test.txt"
+    assert result[0]["ref_count"] == 1
+    assert result[0]["alt_count"] == 1
     # Cleanup
     os.remove("result_HERC2_TEST_ID.tsv")
diff --git a/examples/herc2/herc2-classifier/assets/aggregate_population_stats.py b/examples/herc2/herc2-classifier/assets/aggregate_population_stats.py
new file mode 100644
index 0000000..6a940e7
--- /dev/null
+++ b/examples/herc2/herc2-classifier/assets/aggregate_population_stats.py
@@ -0,0 +1,144 @@
+import argparse
+import csv
+import re
+from collections import defaultdict
+
+def parse_args():
+    parser = argparse.ArgumentParser(description="Aggregate population allele statistics")
+    parser.add_argument("--input", required=True, help="Input TSV from combined classifier output")
+    parser.add_argument("--output", required=True, help="Output TSV path")
+    return parser.parse_args()
+
+def locus_key_for_row(row):
+    chrom = (row.get("chromosome") or "").strip()
+    pos = (row.get("position") or "").strip()
+    ref = (row.get("ref") or "").strip()
+    alt = (row.get("alt") or "").strip()
+    if not (chrom and pos and ref and alt):
+        return None
+    return f"{chrom}-{pos}-{ref}-{alt}"
+
+def to_int(value):
+    try:
+        return int(value)
+    except Exception:
+        return 0
+
+def parse_alleles(genotype, alleles):
+    if not genotype:
+        return []
+    genotype = genotype.strip()
+    if not genotype:
+        return []
+
+    # Split on common genotype separators
+    if "/" in genotype or "|" in genotype:
+        parts = [p for p in re.split(r"[\/|]", genotype) if p]
+        return parts
+
+    # If alleles are same length and genotype is a concat of two alleles, split evenly
+    if alleles:
+        lengths = {len(a) for a in alleles if a}
+        if len(lengths) == 1:
+            allele_len = lengths.pop()
+            if allele_len > 0 and len(genotype) == 2 * allele_len:
+                return [genotype[:allele_len], genotype[allele_len:]]
+
+    # Fallback for single-base alleles like "AA" or "AG"
+    if len(genotype) == 2:
+        return [genotype[0], genotype[1]]
+
+    return [genotype]
+
+def main():
+    args = parse_args()
+
+    # stats keyed by (locus_base, allele)
+    stats = defaultdict(lambda: {
+        "allele_count": 0,
+        "num_homo": 0,
+        "num_hetero": 0,
+        "rsid": None,
+    })
+    locus_called_samples = defaultdict(int)
+
+    with open(args.input, "r", encoding="utf-8") as fh:
+        reader = csv.DictReader(fh, delimiter="\t")
+        for row in reader:
+            match_type = (row.get("match_type") or "").strip()
+            if match_type.lower() == "no call":
+                continue
+
+            locus_key = locus_key_for_row(row)
+            if locus_key is None:
+                continue
+
+            alt_count = to_int(row.get("alt_count"))
+            ref_count = to_int(row.get("ref_count"))
+            allele_number = ref_count + alt_count
+
+            if allele_number <= 0:
+                continue
+
+            chrom = (row.get("chromosome") or "").strip()
+            pos = (row.get("position") or "").strip()
+            ref = (row.get("ref") or "").strip()
+            alt = (row.get("alt") or "").strip()
+            locus_base = f"{chrom}-{pos}"
+
+            alleles = []
+            if ref:
+                alleles.append(ref)
+            if alt:
+                alleles.extend([a.strip() for a in alt.split(",") if a.strip()])
+
+            genotype = (row.get("genotype") or "").strip()
+            gt_alleles = parse_alleles(genotype, alleles)
+            if not gt_alleles:
+                continue
+
+            locus_called_samples[locus_base] += 1
+
+            rsid = row.get("rsid")
+            is_homo = len(gt_alleles) == 2 and gt_alleles[0] == gt_alleles[1]
+
+            for allele in gt_alleles:
+                key = (locus_base, allele)
+                entry = stats[key]
+                entry["allele_count"] += 1
+                if is_homo and allele == gt_alleles[0]:
+                    entry["num_homo"] += 1
+                elif not is_homo:
+                    entry["num_hetero"] += 1
+                if rsid and not entry["rsid"]:
+                    entry["rsid"] = rsid
+
+    with open(args.output, "w", encoding="utf-8", newline="") as out_fh:
+        fieldnames = [
+            "locus_key",
+            "allele_count",
+            "allele_number",
+            "num_homo",
+            "num_hetero",
+            "allele_freq",
+            "rsid",
+        ]
+        writer = csv.DictWriter(out_fh, fieldnames=fieldnames, delimiter="\t")
+        writer.writeheader()
+        for (locus_base, allele) in sorted(stats.keys()):
+            entry = stats[(locus_base, allele)]
+            called = locus_called_samples.get(locus_base, 0)
+            allele_number = called * 2
+            allele_freq = (entry["allele_count"] / allele_number) if allele_number else 0
+            writer.writerow({
+                "locus_key": f"{locus_base}-{allele}",
+                "allele_count": entry["allele_count"],
+                "allele_number": allele_number,
+                "num_homo": entry["num_homo"],
+                "num_hetero": entry["num_hetero"],
+                "allele_freq": f"{allele_freq:.6f}",
+                "rsid": entry["rsid"],
+            })
+
+if __name__ == "__main__":
+    main()
diff --git a/examples/herc2/herc2-classifier/assets/classify_herc2.py b/examples/herc2/herc2-classifier/assets/classify_herc2.py
index fc5112d..393aae1 100644
--- a/examples/herc2/herc2-classifier/assets/classify_herc2.py
+++ b/examples/herc2/herc2-classifier/assets/classify_herc2.py
@@ -10,6 +10,15 @@
 # (A;G) also tends toward brown.
 # (G;G) gives blue eye color ~99% of the time.
 
+def _format_allele_label(allele):
+    if isinstance(allele, Alleles):
+        return ",".join(sorted(a.value for a in allele))
+    if isinstance(allele, str):
+        return allele
+    if hasattr(allele, "__iter__"):
+        return ",".join(sorted(str(a) for a in allele))
+    return str(allele)
+
 class HERC2Classifier(GenotypeClassifier):
     def classify(self, matches):
         match = matches.get(rs12913832)
@@ -25,10 +34,14 @@ def classify(self, matches):
             result = "No call"
             genotype_sorted = None
             match_type = MatchType.NO_CALL.value
+            ref_count = 0
+            alt_count = 0
         else:
             genotype_sorted = match.genotype_sorted
             result = eye_color_map.get(genotype_sorted, "Unknown")
             match_type = match.match_type.value
+            ref_count = match.ref_count
+            alt_count = match.alt_count
         
         # Extract properties from match (source_row has the actual data from the file)
         if match and match.source_row:
@@ -41,15 +54,21 @@ def classify(self, matches):
             position = None
         
         # Create report row using match properties
+        ref_label = _format_allele_label(rs12913832.ref)
+        alt_label = _format_allele_label(rs12913832.alt)
         report_row = {
             "participant_id": self.participant_id,
             "filename": self.filename,
             "rsid": rsid,
             "chromosome": chromosome,
             "position": position,
+            "ref": ref_label,
+            "alt": alt_label,
             "genotype": genotype_sorted,
             "match_type": match_type,
             "eye_color": result,
+            "ref_count": ref_count,
+            "alt_count": alt_count,
         }
         
         # Write to TSV file (as a list with one row)
@@ -93,6 +112,8 @@ def test_brown_homozygous():
     assert result[0]["rsid"] == "rs12913832"
     assert result[0]["chromosome"] == "15"
     assert result[0]["position"] == 28120472
+    assert result[0]["ref_count"] == 2
+    assert result[0]["alt_count"] == 0
     # Cleanup
     os.remove("result_HERC2_TEST_ID.tsv")
 
@@ -104,6 +125,8 @@ def test_brown_heterozygous_unsorted():
     assert result[0]["match_type"] == MatchType.VARIANT_CALL.value
     assert result[0]["participant_id"] == "TEST_ID"
     assert result[0]["filename"] == "test.txt"
+    assert result[0]["ref_count"] == 1
+    assert result[0]["alt_count"] == 1
     # Cleanup
     os.remove("result_HERC2_TEST_ID.tsv")
 
@@ -115,6 +138,8 @@ def test_blue_homozygous():
     assert result[0]["match_type"] == MatchType.VARIANT_CALL.value
     assert result[0]["participant_id"] == "TEST_ID"
     assert result[0]["filename"] == "test.txt"
+    assert result[0]["ref_count"] == 0
+    assert result[0]["alt_count"] == 2
     # Cleanup
     os.remove("result_HERC2_TEST_ID.tsv")
 
@@ -126,11 +151,13 @@ def test_no_call():
     assert result[0]["match_type"] == MatchType.NO_CALL.value
     assert result[0]["participant_id"] == "TEST_ID"
     assert result[0]["filename"] == "test.txt"
+    assert result[0]["ref_count"] == 0
+    assert result[0]["alt_count"] == 0
     # Cleanup
     os.remove("result_HERC2_TEST_ID.tsv")
 
 def test_unexpected_allele_c():
-    """Test handling of unexpected C allele (not in reference map)."""
+    'Test handling of unexpected C allele (not in reference map).'
     result = classify_fixture("AC")
     assert len(result) == 1
     assert result[0]["eye_color"] == "Unknown"
@@ -138,5 +165,7 @@ def test_unexpected_allele_c():
     assert result[0]["match_type"] == MatchType.VARIANT_CALL.value
     assert result[0]["participant_id"] == "TEST_ID"
     assert result[0]["filename"] == "test.txt"
+    assert result[0]["ref_count"] == 1
+    assert result[0]["alt_count"] == 1
     # Cleanup
     os.remove("result_HERC2_TEST_ID.tsv")
diff --git a/examples/herc2/herc2-classifier/flow.yaml b/examples/herc2/herc2-classifier/flow.yaml
index 797846d..d0eb9eb 100644
--- a/examples/herc2/herc2-classifier/flow.yaml
+++ b/examples/herc2/herc2-classifier/flow.yaml
@@ -4,22 +4,23 @@ metadata:
   name: herc2-classifier
   version: 0.1.1
 spec:
+  steps:
+  - id: herc2
+    uses:
+      source:
+        kind: local
+        path: ./
+    with:
+      participants: inputs.samplesheet
+    publish:
+      classification_result: File(result_HERC2.tsv)
+      population_stats: File(result_HERC2_stats.tsv)
+    store:
+      counts_sql:
+        kind: sql
+        source: classification_result
+        table: herc2_{run_id}
+        key_column: participant_id
   inputs:
     samplesheet:
       type: List[GenotypeRecord]
-  steps:
-    - id: herc2
-      uses:
-        source:
-          kind: local
-          path: ./
-      with:
-        participants: inputs.samplesheet
-      publish:
-        classification_result: File(result_HERC2.tsv)
-      store:
-        counts_sql:
-          kind: sql
-          source: classification_result
-          table: herc2_{run_id}
-          key_column: participant_id
diff --git a/examples/herc2/herc2-classifier/module.yaml b/examples/herc2/herc2-classifier/module.yaml
index 21224f0..1519428 100644
--- a/examples/herc2/herc2-classifier/module.yaml
+++ b/examples/herc2/herc2-classifier/module.yaml
@@ -3,30 +3,38 @@ kind: Module
 metadata:
   name: herc2-classifier
   version: 0.1.1
-  description: Classification of HERC2 genotypes for eye color prediction.
   authors:
-    - madhava@openmined.org
+  - madhava@openmined.org
+  description: Classification of HERC2 genotypes for eye color prediction.
 spec:
   runner:
     kind: nextflow
     entrypoint: workflow.nf
     template: dynamic-nextflow
-  assets:
-    - path: classify_herc2.py
+    image: ghcr.io/openmined/bioscript:0.1.6
   inputs:
-    - name: participants
-      type: List[GenotypeRecord]
-      description: CSV/TSV with participant_id and genotype_file columns
-      format:
-        kind: csv
-        mapping:
-          participant_id: participant_id
-          genotype_file: genotype_file
+  - name: participants
+    type: List[GenotypeRecord]
+    description: CSV/TSV with participant_id and genotype_file columns
+    format:
+      kind: csv
+      mapping:
+        participant_id: participant_id
+        genotype_file: genotype_file
   outputs:
-    - name: classification_result
-      type: File
-      description: HERC2 eye color classification (aggregated)
-      format:
-        kind: tsv
-      path: result_HERC2.tsv
+  - name: classification_result
+    type: File
+    description: HERC2 eye color classification (aggregated)
+    format:
+      kind: tsv
+    path: result_HERC2.tsv
+  - name: population_stats
+    type: File
+    description: HERC2 population allele statistics (aggregated)
+    format:
+      kind: tsv
+    path: result_HERC2_stats.tsv
   parameters: []
+  assets:
+  - path: classify_herc2.py
+  - path: aggregate_population_stats.py
diff --git a/examples/herc2/herc2-classifier/workflow.nf b/examples/herc2/herc2-classifier/workflow.nf
index ff56507..f01addc 100644
--- a/examples/herc2/herc2-classifier/workflow.nf
+++ b/examples/herc2/herc2-classifier/workflow.nf
@@ -33,8 +33,15 @@ workflow USER {
             per_participant_results.collect()
         )
 
+        // Aggregate population statistics
+        def population_stats_ch = aggregate_population_stats(
+            Channel.value(assetsDirPath),
+            aggregated
+        )
+
     emit:
         classification_result = aggregated
+        population_stats = population_stats_ch
 }
 
 process herc2_classifier {
@@ -74,3 +81,20 @@ process aggregate_results {
     bioscript combine --list results.list --output result_HERC2.tsv
     """
 }
+
+process aggregate_population_stats {
+    container 'ghcr.io/openmined/bioscript:0.1.6'
+    publishDir params.results_dir, mode: 'copy', overwrite: true
+
+    input:
+        path assets_dir
+        path aggregated_results
+
+    output:
+        path "result_HERC2_stats.tsv"
+
+    script:
+    """
+    python3 "${assets_dir}/aggregate_population_stats.py"       --input "${aggregated_results}"       --output result_HERC2_stats.tsv
+    """
+}
diff --git a/examples/herc2/herc2_dev.ipynb b/examples/herc2/herc2_dev.ipynb
index 500fca5..5cee6a5 100644
--- a/examples/herc2/herc2_dev.ipynb
+++ b/examples/herc2/herc2_dev.ipynb
@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "66a0c985-275c-4213-902b-45f5c188d9dd",
    "metadata": {},
    "outputs": [],
@@ -22,7 +22,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "b025ff95-b911-4b42-8f63-35567637dfb9",
    "metadata": {},
    "outputs": [],
@@ -34,7 +34,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "014b798d-a680-461b-822b-b3c72c504488",
    "metadata": {},
    "outputs": [],
@@ -50,11 +50,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "fbf79259-7445-4284-a17a-a8f584914f80",
    "metadata": {},
    "outputs": [],
    "source": [
+    "def _format_allele_label(allele):\n",
+    "    if isinstance(allele, Alleles):\n",
+    "        return \",\".join(sorted(a.value for a in allele))\n",
+    "    if isinstance(allele, str):\n",
+    "        return allele\n",
+    "    if hasattr(allele, \"__iter__\"):\n",
+    "        return \",\".join(sorted(str(a) for a in allele))\n",
+    "    return str(allele)\n",
+    "\n",
     "class HERC2Classifier(GenotypeClassifier):\n",
     "    def classify(self, matches):\n",
     "        match = matches.get(rs12913832)\n",
@@ -70,10 +79,14 @@
     "            result = \"No call\"\n",
     "            genotype_sorted = None\n",
     "            match_type = MatchType.NO_CALL.value\n",
+    "            ref_count = 0\n",
+    "            alt_count = 0\n",
     "        else:\n",
     "            genotype_sorted = match.genotype_sorted\n",
     "            result = eye_color_map.get(genotype_sorted, \"Unknown\")\n",
     "            match_type = match.match_type.value\n",
+    "            ref_count = match.ref_count\n",
+    "            alt_count = match.alt_count\n",
     "        \n",
     "        # Extract properties from match (source_row has the actual data from the file)\n",
     "        if match and match.source_row:\n",
@@ -86,27 +99,33 @@
     "            position = None\n",
     "        \n",
     "        # Create report row using match properties\n",
+    "        ref_label = _format_allele_label(rs12913832.ref)\n",
+    "        alt_label = _format_allele_label(rs12913832.alt)\n",
     "        report_row = {\n",
     "            \"participant_id\": self.participant_id,\n",
     "            \"filename\": self.filename,\n",
     "            \"rsid\": rsid,\n",
     "            \"chromosome\": chromosome,\n",
     "            \"position\": position,\n",
+    "            \"ref\": ref_label,\n",
+    "            \"alt\": alt_label,\n",
     "            \"genotype\": genotype_sorted,\n",
     "            \"match_type\": match_type,\n",
     "            \"eye_color\": result,\n",
+    "            \"ref_count\": ref_count,\n",
+    "            \"alt_count\": alt_count,\n",
     "        }\n",
     "        \n",
     "        # Write to TSV file (as a list with one row)\n",
     "        write_tsv(f\"{self.output_basename}.tsv\", [report_row])\n",
     "        \n",
     "        # Return list for testing (consistent with BRCA)\n",
-    "        return [report_row]"
+    "        return [report_row]\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "id": "9db0d015-66d4-4564-ae99-e1353dad1aef",
    "metadata": {},
    "outputs": [],
@@ -120,7 +139,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "id": "2794c5cf-6361-4743-ac7c-10dd370b47f2",
    "metadata": {},
    "outputs": [],
@@ -138,7 +157,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "id": "48cdc397-62fd-473e-af2f-fec6d1ac21c8",
    "metadata": {},
    "outputs": [],
@@ -162,6 +181,8 @@
     "    assert result[0][\"rsid\"] == \"rs12913832\"\n",
     "    assert result[0][\"chromosome\"] == \"15\"\n",
     "    assert result[0][\"position\"] == 28120472\n",
+    "    assert result[0][\"ref_count\"] == 2\n",
+    "    assert result[0][\"alt_count\"] == 0\n",
     "    # Cleanup\n",
     "    os.remove(\"result_HERC2_TEST_ID.tsv\")\n",
     "\n",
@@ -173,6 +194,8 @@
     "    assert result[0][\"match_type\"] == MatchType.VARIANT_CALL.value\n",
     "    assert result[0][\"participant_id\"] == \"TEST_ID\"\n",
     "    assert result[0][\"filename\"] == \"test.txt\"\n",
+    "    assert result[0][\"ref_count\"] == 1\n",
+    "    assert result[0][\"alt_count\"] == 1\n",
     "    # Cleanup\n",
     "    os.remove(\"result_HERC2_TEST_ID.tsv\")\n",
     "\n",
@@ -184,6 +207,8 @@
     "    assert result[0][\"match_type\"] == MatchType.VARIANT_CALL.value\n",
     "    assert result[0][\"participant_id\"] == \"TEST_ID\"\n",
     "    assert result[0][\"filename\"] == \"test.txt\"\n",
+    "    assert result[0][\"ref_count\"] == 0\n",
+    "    assert result[0][\"alt_count\"] == 2\n",
     "    # Cleanup\n",
     "    os.remove(\"result_HERC2_TEST_ID.tsv\")\n",
     "\n",
@@ -195,11 +220,13 @@
     "    assert result[0][\"match_type\"] == MatchType.NO_CALL.value\n",
     "    assert result[0][\"participant_id\"] == \"TEST_ID\"\n",
     "    assert result[0][\"filename\"] == \"test.txt\"\n",
+    "    assert result[0][\"ref_count\"] == 0\n",
+    "    assert result[0][\"alt_count\"] == 0\n",
     "    # Cleanup\n",
     "    os.remove(\"result_HERC2_TEST_ID.tsv\")\n",
     "\n",
     "def test_unexpected_allele_c():\n",
-    "    \"\"\"Test handling of unexpected C allele (not in reference map).\"\"\"\n",
+    "    'Test handling of unexpected C allele (not in reference map).'\n",
     "    result = classify_fixture(\"AC\")\n",
     "    assert len(result) == 1\n",
     "    assert result[0][\"eye_color\"] == \"Unknown\"\n",
@@ -207,16 +234,26 @@
     "    assert result[0][\"match_type\"] == MatchType.VARIANT_CALL.value\n",
     "    assert result[0][\"participant_id\"] == \"TEST_ID\"\n",
     "    assert result[0][\"filename\"] == \"test.txt\"\n",
+    "    assert result[0][\"ref_count\"] == 1\n",
+    "    assert result[0][\"alt_count\"] == 1\n",
     "    # Cleanup\n",
-    "    os.remove(\"result_HERC2_TEST_ID.tsv\")"
+    "    os.remove(\"result_HERC2_TEST_ID.tsv\")\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "id": "d3a03b87-9882-49e5-bdb7-55a3f7834770",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "✓ All tests passed!\n"
+     ]
+    }
+   ],
    "source": [
     "# Run tests\n",
     "test_brown_homozygous()\n",
@@ -229,10 +266,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "id": "b36a3d84-91a6-4a8f-84e0-6c43f6055c23",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "============================================================\n",
+      "Testing: classify_herc2.py\n",
+      "============================================================\n",
+      "Running tests with pytest: classify_herc2.py\n",
+      "\u001b[1m============================= test session starts ==============================\u001b[0m\n",
+      "platform darwin -- Python 3.13.5, pytest-9.0.2, pluggy-1.6.0 -- /Users/madhavajay/dev/biovault-desktop/workspace8/bioscript/.venv/bin/python3\n",
+      "cachedir: .pytest_cache\n",
+      "rootdir: /Users/madhavajay/dev/biovault-desktop/workspace8/bioscript/examples/herc2\n",
+      "plugins: anyio-4.12.1\n",
+      "collected 5 items                                                              \u001b[0m\n",
+      "\n",
+      "classify_herc2.py::test_brown_homozygous \u001b[32mPASSED\u001b[0m\u001b[32m                          [ 20%]\u001b[0m\n",
+      "classify_herc2.py::test_brown_heterozygous_unsorted \u001b[32mPASSED\u001b[0m\u001b[32m               [ 40%]\u001b[0m\n",
+      "classify_herc2.py::test_blue_homozygous \u001b[32mPASSED\u001b[0m\u001b[32m                           [ 60%]\u001b[0m\n",
+      "classify_herc2.py::test_no_call \u001b[32mPASSED\u001b[0m\u001b[32m                                   [ 80%]\u001b[0m\n",
+      "classify_herc2.py::test_unexpected_allele_c \u001b[32mPASSED\u001b[0m\u001b[32m                       [100%]\u001b[0m\n",
+      "\n",
+      "\u001b[32m============================== \u001b[32m\u001b[1m5 passed\u001b[0m\u001b[32m in 0.01s\u001b[0m\u001b[32m ===============================\u001b[0m\n"
+     ]
+    }
+   ],
    "source": [
     "from bioscript import export_from_notebook\n",
     "export_from_notebook(\"herc2_dev.ipynb\", \"classify_herc2.py\")\n",
@@ -242,10 +305,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "id": "hrvdxb063",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Test file created: herc2_test_ga.tsv\n",
+      "Content:\n",
+      "# rsid\tchromosome\tposition\tgenotype\n",
+      "rs12913832\t15\t28120472\tGA\n",
+      "✓ Test passed and file created!\n"
+     ]
+    }
+   ],
    "source": [
     "# Rewritten to write the raw line to a file and use bioscript classify in the next cell\n",
     "from pathlib import Path\n",
@@ -269,10 +344,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "id": "c51e4f6f-9900-4e7c-844e-211a165f69ef",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[bioscript] Current working directory: /Users/madhavajay/dev/biovault-desktop/workspace8/bioscript/examples/herc2\n",
+      "[bioscript] Provided SNP file argument: herc2_test_ga.tsv\n",
+      "[bioscript] Provided path absolute? False\n",
+      "[bioscript] Resolved SNP path: /Users/madhavajay/dev/biovault-desktop/workspace8/bioscript/examples/herc2/herc2_test_ga.tsv\n",
+      "[bioscript] Resolved exists? True\n",
+      "[bioscript] CWD contents: .DS_Store, .ipynb_checkpoints, .pytest_cache, __pycache__, classify_herc2.py, herc2-classifier, herc2_dev.ipynb, herc2_test_ga.tsv, result_HERC2_X.tsv, result_HERC2_test_user.tsv\n",
+      "[bioscript] Using resolved SNP path: /Users/madhavajay/dev/biovault-desktop/workspace8/bioscript/examples/herc2/herc2_test_ga.tsv\n",
+      "participant_id=X\n",
+      "HERC2_count=1\n",
+      "participant_id\tfilename\trsid\tchromosome\tposition\tref\talt\tgenotype\tmatch_type\teye_color\tref_count\talt_count\n",
+      "X\therc2_test_ga.tsv\trs12913832\t15\t28120472\tA\tC,G,T,U\tAG\tVariant call\tBrown\t1\t1\n"
+     ]
+    }
+   ],
    "source": [
     "!bioscript classify classify_herc2.py --file herc2_test_ga.tsv --participant_id=\"X\"\n",
     "!cat result_HERC2_X.tsv"
@@ -280,10 +373,44 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "id": "7830775c-a21a-40f6-acd1-262261e3b0f6",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[bioscript] Current working directory: /Users/madhavajay/dev/biovault-desktop/workspace8/bioscript/examples/herc2\n",
+      "[bioscript] Provided SNP file argument: herc2_test_ga.tsv\n",
+      "[bioscript] Provided path absolute? False\n",
+      "[bioscript] Resolved SNP path: /Users/madhavajay/dev/biovault-desktop/workspace8/bioscript/examples/herc2/herc2_test_ga.tsv\n",
+      "[bioscript] Resolved exists? True\n",
+      "[bioscript] CWD contents: .DS_Store, .ipynb_checkpoints, .pytest_cache, __pycache__, classify_herc2.py, herc2-classifier, herc2_dev.ipynb, herc2_test_ga.tsv, result_HERC2_X.tsv, result_HERC2_test_user.tsv\n",
+      "[bioscript] Using resolved SNP path: /Users/madhavajay/dev/biovault-desktop/workspace8/bioscript/examples/herc2/herc2_test_ga.tsv\n",
+      "{\n",
+      "  \"participant_id\": \"test_user\",\n",
+      "  \"HERC2_count\": 1,\n",
+      "  \"HERC2_data\": [\n",
+      "    {\n",
+      "      \"participant_id\": \"test_user\",\n",
+      "      \"filename\": \"herc2_test_ga.tsv\",\n",
+      "      \"rsid\": \"rs12913832\",\n",
+      "      \"chromosome\": \"15\",\n",
+      "      \"position\": 28120472,\n",
+      "      \"ref\": \"A\",\n",
+      "      \"alt\": \"C,G,T,U\",\n",
+      "      \"genotype\": \"AG\",\n",
+      "      \"match_type\": \"Variant call\",\n",
+      "      \"eye_color\": \"Brown\",\n",
+      "      \"ref_count\": 1,\n",
+      "      \"alt_count\": 1\n",
+      "    }\n",
+      "  ]\n",
+      "}\n"
+     ]
+    }
+   ],
    "source": [
     "# Test JSON output to show the new consistent naming convention\n",
     "!bioscript classify classify_herc2.py --file herc2_test_ga.tsv --out json --participant_id=\"test_user\""
@@ -299,10 +426,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "id": "5c543421",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "BioVaultProject(name='herc2-classifier', author='madhava@openmined.org', workflow='workflow.nf', description='Classification of HERC2 genotypes for eye color prediction.', template=<TemplateType.DYNAMIC_NEXTFLOW: 'dynamic-nextflow'>, version='0.1.1', assets=['classify_herc2.py', 'aggregate_population_stats.py'], parameters=[], inputs=[Input(name='participants', type='List[GenotypeRecord]', description='CSV/TSV with participant_id and genotype_file columns', format='csv', path=None, mapping={'participant_id': 'participant_id', 'genotype_file': 'genotype_file'}, cli_flag=None)], outputs=[Output(name='classification_result', type='File', description='HERC2 eye color classification (aggregated)', format='tsv', path='result_HERC2.tsv', cli_flag=None), Output(name='population_stats', type='File', description='HERC2 population allele statistics (aggregated)', format='tsv', path='result_HERC2_stats.tsv', cli_flag=None)], processes=[ProcessDefinition(name='herc2_classifier', script='classify_herc2.py', container='ghcr.io/openmined/bioscript:0.1.6', kind='bioscript')], docker_image='ghcr.io/openmined/bioscript:0.1.6', docker_platform='linux/amd64')"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "from pathlib import Path\n",
     "from bioscript import export_bioscript_workflow\n",
@@ -313,7 +451,7 @@
     "    workflow_name='herc2-classifier',\n",
     "    author='madhava@openmined.org',\n",
     "    target_dir=\"./\",\n",
-    "    assets={},\n",
+    "    assets=['herc2-classifier/assets/aggregate_population_stats.py'],\n",
     "    inputs=[\n",
     "        {\n",
     "            'name': 'participants',\n",
@@ -334,19 +472,96 @@
     "            'format': 'tsv',\n",
     "            'path': 'result_HERC2.tsv',\n",
     "        },\n",
+    "        {\n",
+    "            'name': 'population_stats',\n",
+    "            'type': 'File',\n",
+    "            'description': 'HERC2 population allele statistics (aggregated)',\n",
+    "            'format': 'tsv',\n",
+    "            'path': 'result_HERC2_stats.tsv',\n",
+    "        },\n",
     "    ],\n",
     "    version=\"0.1.1\",\n",
     "    description=\"Classification of HERC2 genotypes for eye color prediction.\",\n",
     ")\n",
-    "project"
+    "project\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
+   "id": "730842a1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2819"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from pathlib import Path\n",
+    "\n",
+    "workflow_path = Path('herc2-classifier/workflow.nf')\n",
+    "if not workflow_path.exists():\n",
+    "    raise FileNotFoundError('workflow.nf not found. Run the export cell first.')\n",
+    "\n",
+    "text = workflow_path.read_text(encoding='utf-8')\n",
+    "\n",
+    "if 'aggregate_population_stats' not in text:\n",
+    "    text = text.replace(\n",
+    "        \"        def aggregated = aggregate_results(\\n            per_participant_results.collect()\\n        )\\n\\n    emit:\\n        classification_result = aggregated\\n}\\n\",\n",
+    "        \"        def aggregated = aggregate_results(\\n            per_participant_results.collect()\\n        )\\n\\n        // Aggregate population statistics\\n        def population_stats_ch = aggregate_population_stats(\\n            Channel.value(assetsDirPath),\\n            aggregated\\n        )\\n\\n    emit:\\n        classification_result = aggregated\\n        population_stats = population_stats_ch\\n}\\n\",\n",
+    "    )\n",
+    "\n",
+    "process_block = '''\n",
+    "process aggregate_population_stats {\n",
+    "    container 'ghcr.io/openmined/bioscript:0.1.6'\n",
+    "    publishDir params.results_dir, mode: 'copy', overwrite: true\n",
+    "\n",
+    "    input:\n",
+    "        path assets_dir\n",
+    "        path aggregated_results\n",
+    "\n",
+    "    output:\n",
+    "        path \\\"result_HERC2_stats.tsv\\\"\n",
+    "\n",
+    "    script:\n",
+    "    \"\"\"\n",
+    "    python3 \"${assets_dir}/aggregate_population_stats.py\" \\\n",
+    "      --input \"${aggregated_results}\" \\\n",
+    "      --output result_HERC2_stats.tsv\n",
+    "    \"\"\"\n",
+    "}\n",
+    "'''\n",
+    "\n",
+    "if 'process aggregate_population_stats' not in text:\n",
+    "    text += process_block\n",
+    "\n",
+    "workflow_path.write_text(text, encoding='utf-8')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
    "id": "3d78cdd5",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "BioVaultPipeline(name='herc2-classifier', inputs={'samplesheet': 'List[GenotypeRecord]'}, steps=[PipelineStep(step_id='herc2', uses='./', with_args={'participants': 'inputs.samplesheet'}, publish={'classification_result': 'File(result_HERC2.tsv)', 'population_stats': 'File(result_HERC2_stats.tsv)'}, store={'counts_sql': SQLStore(source='classification_result', table_name='herc2_{run_id}', destination='SQL()', participant_column='participant_id', key_column='participant_id')})], version='0.1.1')"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "from bioscript import export_bioscript_pipeline, PipelineStep, SQLStore\n",
     "\n",
@@ -365,6 +580,7 @@
     "            },\n",
     "            publish={\n",
     "                'classification_result': 'File(result_HERC2.tsv)',\n",
+    "                'population_stats': 'File(result_HERC2_stats.tsv)',\n",
     "            },\n",
     "            store={\n",
     "                'counts_sql': SQLStore(\n",
@@ -398,7 +614,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.7"
+   "version": "3.13.5"
   }
  },
  "nbformat": 4,
diff --git a/python/src/bioscript/biovault.py b/python/src/bioscript/biovault.py
index 662ff46..58a6b1f 100644
--- a/python/src/bioscript/biovault.py
+++ b/python/src/bioscript/biovault.py
@@ -760,10 +760,11 @@ def _generate_participant_workflow_nf(self, entrypoint: Optional[str] = None) ->
                 if "{participant_id}" in output_spec.path:
                     individual_pattern = output_spec.path.replace("{participant_id}", "*")
                 else:
-                    aggregated_path = output_spec.path
-                    # Extract classifier name from aggregated path (e.g., result_HERC2.tsv -> HERC2)
-                    if aggregated_path.startswith("result_") and aggregated_path.endswith(".tsv"):
-                        classifier_name = aggregated_path[7:-4]  # Remove "result_" and ".tsv"
+                    if aggregated_path is None:
+                        aggregated_path = output_spec.path
+                        # Extract classifier name from aggregated path (e.g., result_HERC2.tsv -> HERC2)
+                        if aggregated_path.startswith("result_") and aggregated_path.endswith(".tsv"):
+                            classifier_name = aggregated_path[7:-4]  # Remove "result_" and ".tsv"
 
         if not classifier_name:
             classifier_name = self.name.upper().replace("-", "_").replace(" ", "_")
@@ -1077,10 +1078,14 @@ def export(
                 raise FileNotFoundError(f"Asset source not found: {src_path}")
             dst_path = assets_dir / asset
             dst_path.parent.mkdir(parents=True, exist_ok=True)
-            if src_path.is_dir():
-                shutil.copytree(src_path, dst_path, dirs_exist_ok=True)
-            else:
-                shutil.copy2(src_path, dst_path)
+            try:
+                if src_path.is_dir():
+                    shutil.copytree(src_path, dst_path, dirs_exist_ok=True)
+                else:
+                    shutil.copy2(src_path, dst_path)
+            except shutil.SameFileError:
+                # Asset already in place (common when exporting into project dir)
+                pass
             copied_assets.add(asset)
 
         # Export notebook if provided