PGx: full call detail (PGX-016..020, 027/028, 031), pgx coverage (PGX-009/035), full HGVS

- supporting_variants.tsv, unresolved_variants.tsv, variants_not_covered.tsv with PGX-026 metadata; per-allele
  supporting/unresolved sites for both alleles of every candidate; variant_change vs top, distant_alternative,
  unexplained_variants, alleles_impacted_by_no_call, alleles_tested.
- simurg pgx coverage: callable / not_covered / masked / equivalent_to per allele and manifest.
- HGVS on GRCh38 RefSeq accessions (NC_...:g.).

Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01814GKVzZVL3FuF3DeiZXhv

src/simurg/pipeline/pgx_pheno.py

@@ -98,15 +98,24 @@ def run_phenotype(o: PhenoOptions, rep: Reporter) -> int:
             else:
                 res, per = gene_phenotype(t, feas)
             flags = list(g.get("flags", [])) + (res.flags if res else [])
-            entry = {"gene": g["gene"], "call_type": "star_allele", "genotype": g["genotype"],
+            top = g["candidates"][0] if g["candidates"] else {}
+            top_alleles = top.get("alleles", [])
+            entry = {"gene": g["gene"], "call_type": g.get("call_type", "star_allele"), "genotype": g["genotype"],
                      "feasible_solutions": g["feasible_solutions"],
                      "activity_score": res.activity_score if res else None,
                      "phenotype": res.phenotype if res else None, "per_solution_phenotypes": per,
-                     "score": g["candidates"][0]["score"] if g["candidates"] else None,
-                     "raw_score": g["candidates"][0]["raw_score"] if g["candidates"] else None,
+                     "score": top.get("score"), "raw_score": top.get("raw_score"),
                      "flags": sorted(set(flags)), "copy_number": g.get("copy_number"),
-                     "candidate_solutions": [{"rank": i + 1, **c} for i, c in enumerate(g["candidates"])],
-                     "alleles_tested": sorted(tested.get(g["gene"], []), key=_natural)}  # fmt: skip
+                     "array_equivalent_alleles": [{"allele": a["allele"], "equivalents": a["array_equivalent_alleles"]}
+                                                  for a in top_alleles],
+                     "supporting_variants": [v for a in top_alleles for v in a["supporting_variants"]],
+                     "variant_no_calls": g.get("variant_no_calls", []),
+                     "variants_not_covered": g.get("variants_not_covered", []),
+                     "unexplained_variants": g.get("unexplained_variants", []),
+                     "candidate_solutions": [{"rank": i + 1, **c, "phenotype": _pheno_of(tables.get(g["gene"]), c)}
+                                             for i, c in enumerate(g["candidates"])],
+                     "alleles_tested": g.get("alleles_tested")
+                     or sorted(tested.get(g["gene"], []), key=_natural)}  # fmt: skip
             genes.append(entry)
             ann_rows.append({"sample_id": s["sample_id"], "sample_name": s.get("sample_name", s["sample_id"]),
                              "gene": g["gene"], "guideline": o.guideline, "genotype": g["genotype"],
@@ -126,6 +135,12 @@ def run_phenotype(o: PhenoOptions, rep: Reporter) -> int:
     return ExitCode.OK
 
 
+def _pheno_of(t: Any, cand: dict[str, Any]) -> str | None:
+    from simurg.pgx.phenotype import phenotype
+
+    return phenotype(t, tuple(cand["genotype"].split("/"))).phenotype if t is not None else None
+
+
 def _natural(a: str) -> tuple[Any, ...]:
     import re