hvantk-resource-msigdb

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Build a Hail Table from an MSigDB GMT gene-set file (e.g., C2 Canonical Pathways) for enrichment / burden / overlap analyses.

bigbio By bigbio schedule Updated 6/4/2026
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name: hvantk:resource-msigdb description: Build a Hail Table from an MSigDB GMT gene-set file (e.g., C2 Canonical Pathways) for enrichment / burden / overlap analyses. status: provisional backend: hail domain: mapping

MSigDB (Molecular Signatures Database)

Read hvantk/skills/_conventions/SKILL.md first. This skill assumes every convention there.

1. Status & scope

  • Status: provisional. The builder, fixture, snapshots, and round-trip test exist; this skill is the design contract and update reference.
  • In scope: any GMT file from MSigDB → single Hail Table keyed by set_name. Verified against the C2 Canonical Pathways human gene-symbols collection (c2.cp.v2026.1.Hs.symbols.gmt, 4,115 sets, 1.6 MB).
  • Out of scope: downloader (MSigDB requires login + license click-through, so per _conventions § 11 acquisition is manual); other MSigDB collections (H, C1, C3-C8) — the builder is collection-agnostic but each collection should be tracked in the catalog separately if onboarded; gene-symbol normalization / alias resolution (use the HGNCGeneCatalogStreamer in hvantk/skills/hgnc/streamers.py downstream); cross-format variants beyond GMT (GMX, XML).

2. Source identity

  • Provider: Broad Institute MSigDB. Variant pinned by this skill's catalog entry: C2 / CP / human / gene symbols / v2026.1.
  • Catalog entry: present. hvantk/resources/registry/genomics/datasets.json contains MSigDB_C2_CP_v2026.1.Hs.symbols (surfaced via hvantk catalog show MSigDB_C2_CP_v2026.1.Hs.symbols). URLs / cadence / license / citation live in the registry entry — not here.

Stable note (not in catalog): MSigDB ships per-collection GMT files. The GMT format is the same across collections, so this builder works for any MSigDB GMT, but each onboarded collection needs its own catalog entry to record license / version / file path.

3. Backend choice + reasoning

backend: hail, domain: mapping. A C2 CP GMT is ~4k rows × variable-width gene columns. Per _conventions § 3 "Lookup / mapping" allows a Hail Table or pandas DataFrame. Hail wins here because downstream consumers (enrichment / burden / overlap, e.g., hvantk/enrichex/) join against Hail Tables keyed on gene symbols — producing a Hail Table avoids re-materialization at every join site, mirroring the HGNC decision. Key by set_name (string, unique-in-file).

Catalog placement note: this skill's catalog entry lives in registry/genomics/datasets.json, not a dedicated mapping/ registry directory (no such directory exists today). The decision is consistent with GWAS_Catalog_v1.0_* (also gene-symbol / variant-adjacent annotation curation) and avoids invasive changes to hvantk/resources/unified_registry.py. Revisit if a mapping/ domain is later introduced.

4. Raw format & gotchas

GMT is tab-separated with variable-width rows:

  • Column 1: set_name (string, unique within a single GMT — e.g., KEGG_APOPTOSIS).
  • Column 2: description text. For MSigDB-issued GMTs this is always a gsea-msigdb URL like https://www.gsea-msigdb.org/gsea/msigdb/human/geneset/KEGG_APOPTOSIS. The spec allows arbitrary text, so the builder preserves it as-is in source_url without parsing. Confirmed against the local 4,115-row source: 100% of rows had a https://www.gsea-msigdb.org/ URL in column 2.
  • Columns 3..N: gene members. For human gene-symbol GMTs (.Hs.symbols.gmt), these are HGNC-approved gene symbols. For other variants (.entrez.gmt, .Mm.symbols.gmt) the contents differ; the builder is symbol-agnostic — it carries strings.

Variable-width-row gotcha (this is the key deviation): hl.import_table rejects rows with inconsistent column counts. Instead, the builder uses hl.import_lines (one row per line, single text: str field) and splits on \t inside the transform. Gene members are sliced as parts[2:] into an array<str>. Set lengths in the source range from 5 (MSigDB minimum) to 1,497 genes; Hail arrays handle this without issue.

Empty-line gotcha: hl.import_lines does yield rows for blank lines (with text == ""). The transform filters set_name == "" after split as a defensive guard.

No type coercions needed — every field is string or array<str> by design.

5. Output contract

  • Object: an AnnotationTable (hvantk/core/models) wrapping a Hail Table, built via AnnotationTable.from_hail(...). The reprocess runner checkpoints it to --output (a .ht directory).
  • Key: [set_name] (string, unique-in-table).
  • Provenance: stamped via ctx.provenance(schema_id="msigdb-genesets-v1"); persisted as a sidecar .provenance.json.
  • Fields:
    • set_name: str — gene-set identifier (e.g., KEGG_APOPTOSIS).
    • source_url: str — GMT column 2, verbatim. For MSigDB-issued GMTs this is a https://www.gsea-msigdb.org/... URL.
    • genes: array<str> — gene members. Order is preserved from the source file.
  • Reference genome: N/A. Gene-set membership is genome-independent; the catalog entry records GRCh38 only because the schema requires it.

Per _conventions § 9, set names are unique-in-table for a single GMT, so no sample_keys.json is maintained — the snapshot test reads keys directly from a small inline list. The post-#101 conventions §9 "unique key, no workaround" rule applies cleanly here.

6. hvantk integration points

  • Builder: build_msigdb_genesets in hvantk/skills/msigdb/builder.py. Signature: (parsed_input, ctx) -> AnnotationTable. The table is built inline (hl.import_lines + split/select/key_by) — there is no _create_table_base helper and no output_path/overwrite kwargs. The shared temp helper, if needed, is cleanup_temp_file in hvantk/core/utils/hail_helpers.py.
  • Registry: declared via the plugin manifest at hvantk/skills/msigdb/plugin.yaml (dataset genesets). The plugin loader (hvantk/core/plugin/loader.py) auto-resolves it from the manifest via get_registry().get_dataset("msigdb:genesets"); there is no TABLE_BUILDERS/MATRIX_BUILDERS registry or adapter. Top-level builds run through run_builder_for_spec (hvantk/core/plugin/run_builder.py).
  • CLI: hvantk reprocess msigdb:genesets --raw-dir <dir> --output <path>.ht --skip-download (msigdb declares no lifecycle.download, so --skip-download is always required; <dir> must contain the unzipped .gmt). The builder takes no --plugin-arg params; no reference-genome arg — gene-set membership is genome-independent.
  • Catalog wiring: see § 2. Downloader: out of scope (manual acquisition).

7. Workflow steps

  1. Resolve raw path. parsed_input is the unzipped .gmt path (resolved by the reprocess runner from --raw-dir). Acquire from https://www.gsea-msigdb.org/gsea/msigdb/human/collections.jsp (login required).
  2. Import. hl.import_lines(paths=str(parsed_input), min_partitions=4) — yields one row per line with text: str.
  3. Transform (inline in build_msigdb_genesets):
    • parts = ht.text.split("\t").
    • set_name = parts[0], source_url = parts[1], genes = parts[2:] (Hail array slice).
    • ht.filter(ht.set_name != "") — defensive against blank lines.
    • ht.key_by("set_name").
  4. Wrap + return. AnnotationTable.from_hail(ht, provenance=ctx.provenance(schema_id="msigdb-genesets-v1")). Checkpointing to --output and provenance sidecar are handled by the reprocess runner.

8. Update playbook

MSigDB releases ~annually (versioned v<year>.<n>, e.g., v2026.1, v2025.1). Per release:

  1. Acquire the new GMT (manual download). Update the file path / version in the corresponding registry/genomics/datasets.json entry; bump accession (MSigDB_C2_CP_v2026.1.Hs.symbols → MSigDB_C2_CP_v2027.1.Hs.symbols).
  2. Re-run the round-trip test (§ 9). If it passes, no builder change.
  3. The GMT format has been stable for ~15 years; column 1 / column 2 / variable-tail shape has not changed. If MSigDB ever changes the description column (column 2) away from a URL, the source_url field name becomes misleading — rename to description and update this skill.
  4. To onboard a different collection (e.g., C5 GO, H Hallmark): add a new catalog entry with the new accession; the same build_msigdb_genesets builder works without modification. Add a parallel fixture and snapshot directory if the new collection has structural quirks (e.g., GMTs with embedded null bytes).

9. Validation contract

Per _conventions § 9:

  • fixture: hvantk/skills/msigdb/tests/testdata/raw/msigdb/c2.cp-sample.gmt. 20 gene sets, ~24 KB, sampled from the v2026.1 C2 CP source by picking representative rows by line index (the GMT format is line-oriented, so a deterministic line subset is a valid sub-GMT). Exercises the short edge (size 5: BIOCARTA, SA), medium sets (60-330 genes), a long set (REACTOME_CELL_CYCLE, 688 genes), and the extra-long tail (REACTOME_POST_TRANSLATIONAL_PROTEIN_MODIFICATION, 1,497 genes). All 20 fixture rows have a https://www.gsea-msigdb.org/ URL in column 2 (matches the live-file invariant).
  • schema_snapshot: hvantk/skills/msigdb/tests/snapshots/schema.json.
  • row_snapshot: hvantk/skills/msigdb/tests/snapshots/sample_rows.json. set_name keys are unique-in-table, so no sample_keys.json is maintained per _conventions § 9 (post-#101). The round-trip test inlines the small key list.
  • test_command: pytest hvantk/skills/msigdb/tests -m hail.

Round-trip test asserts: the built AnnotationTable schema matches schema.json; deterministic sorted row slice matches sample_rows.json. Regenerate snapshots when the schema changes (rare — see § 8).

Install via CLI
npx skills add https://github.com/bigbio/hvantk --skill hvantk-resource-msigdb
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