PGx DB: pgx db build from CPIC (PGX-001..005, IN-053, CLI-035)
- scripts/pgx/fetch_sources.sh: CPIC API tables (CC0) into a dated folder with version and hashes. - simurg/pgx/db.py: CPIC HGVS locations and values -> left-normalised VCF variants (SNV, del, ins, dup, repeats, delins, chrM); IUPAC values are core-allele wildcards; alleles without definitions are flagged. - pipeline/pgx_db.py: deterministic SQLite (content-hash name), probe_map via the SNV VCF site mapper; GSA v4 PGx: 22 genes, 1354 alleles, 5002 probe links; two builds byte-identical.
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@@ -15,6 +15,7 @@ used only as external subprocess oracles and are not copied or linked.
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| [PyO3](https://github.com/PyO3/pyo3), [rust-numpy](https://github.com/PyO3/rust-numpy), [ndarray](https://github.com/rust-ndarray/ndarray) and their Rust dependencies | MIT / Apache-2.0 / BSD-2-Clause | Compiled into the optional `simurg_core` extension (`rust/simurg-core`); list with `cargo tree` |
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| [PyO3](https://github.com/PyO3/pyo3), [rust-numpy](https://github.com/PyO3/rust-numpy), [ndarray](https://github.com/rust-ndarray/ndarray) and their Rust dependencies | MIT / Apache-2.0 / BSD-2-Clause | Compiled into the optional `simurg_core` extension (`rust/simurg-core`); list with `cargo tree` |
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| [UCSC Genome Browser](https://genome.ucsc.edu/) `cytoBand` tables (hg38, hg19) and `ncbiRefSeq` (RefSeq transcripts, NCBI) | Free for all uses (UCSC data terms; RefSeq is public domain) | `simurg/cn/data/cytoBand_GRCh3{7,8}.txt.gz` and the derived centromere/acrocentric mask BEDs are shipped; `scripts/build_annotation_bundle.sh` downloads cytoBand + ncbiRefSeq for gene lists; `simurg/pgx/data/pgx_cn_regions.GRCh38.v1.bed` is derived from ncbiRefSeq exon coordinates (`scripts/pgx/build_cn_regions.py`) |
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| [UCSC Genome Browser](https://genome.ucsc.edu/) `cytoBand` tables (hg38, hg19) and `ncbiRefSeq` (RefSeq transcripts, NCBI) | Free for all uses (UCSC data terms; RefSeq is public domain) | `simurg/cn/data/cytoBand_GRCh3{7,8}.txt.gz` and the derived centromere/acrocentric mask BEDs are shipped; `scripts/build_annotation_bundle.sh` downloads cytoBand + ncbiRefSeq for gene lists; `simurg/pgx/data/pgx_cn_regions.GRCh38.v1.bed` is derived from ncbiRefSeq exon coordinates (`scripts/pgx/build_cn_regions.py`) |
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| [illuminaio](https://github.com/HenrikBengtsson/illuminaio) | GPL-2 | Documentation of IDAT field codes only; oracle via subprocess |
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| [illuminaio](https://github.com/HenrikBengtsson/illuminaio) | GPL-2 | Documentation of IDAT field codes only; oracle via subprocess |
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| [CPIC](https://cpicpgx.org) database via the CPIC API (allele definitions, allele function, diplotype→phenotype tables) | CC0 1.0 | downloaded by `scripts/pgx/fetch_sources.sh` into `data/` (never committed); `simurg pgx db build` derives the local PGx DB from it; source version and file hashes are recorded in the DB `meta` table |
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## BSD-2-Clause (BeadArrayFiles, verbatim from its README)
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## BSD-2-Clause (BeadArrayFiles, verbatim from its README)
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@@ -44,6 +44,7 @@ Generated from `src/simurg/core/errors.py` — do not edit by hand.
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| `E_OUTPUT_EXISTS` | error | Outputs already exist; use --force or --resume | CLI-010 |
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| `E_OUTPUT_EXISTS` | error | Outputs already exist; use --force or --resume | CLI-010 |
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| `E_PGX_BATCH_TOO_SMALL` | error | Too few (passing) samples in the batch for PGx CN calling | PCN-004 |
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| `E_PGX_BATCH_TOO_SMALL` | error | Too few (passing) samples in the batch for PGx CN calling | PCN-004 |
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| `E_PGX_CN_FAILED` | error | PGx CN calling failed for the sample | PCN-002 |
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| `E_PGX_CN_FAILED` | error | PGx CN calling failed for the sample | PCN-002 |
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| `E_PGX_SOURCE` | error | PGx source tables missing; run scripts/pgx/fetch_sources.sh | PGX-001 |
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| `E_PGX_TRAIN_TOO_SMALL` | error | Too few (passing) samples to train a PGx CN model | PCN-005 |
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| `E_PGX_TRAIN_TOO_SMALL` | error | Too few (passing) samples to train a PGx CN model | PCN-005 |
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| `E_QC_CONFIG_EXT` | error | QC config file must be .yaml or .yml | QC-021 |
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| `E_QC_CONFIG_EXT` | error | QC config file must be .yaml or .yml | QC-021 |
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| `E_QC_CONFIG_MISSING` | error | QC config file does not exist | QC-021 |
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| `E_QC_CONFIG_MISSING` | error | QC config file does not exist | QC-021 |
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@@ -0,0 +1,27 @@
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#!/usr/bin/env bash
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# Download the public PGx sources for `simurg pgx db build` (spec PGX-001) into a dated folder.
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# bash scripts/pgx/fetch_sources.sh [OUT_DIR] (default data/pgx/sources)
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# CPIC (CC0): tables from the CPIC API (https://api.cpicpgx.org, PostgREST) as JSON; the newest change-log date is
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# recorded as the data version. Never committed (data/ is ignored).
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set -euo pipefail
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OUT=${1:-data/pgx/sources}
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DATE=$(date -u +%Y%m%d)
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D="$OUT/cpic-$DATE"
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mkdir -p "$D"
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API=https://api.cpicpgx.org/v1
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for t in gene allele allele_definition allele_location_value sequence_location gene_result gene_result_lookup \
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gene_result_diplotype population change_log; do
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curl -sSf --retry 3 -H "Accept: application/json" "$API/$t" -o "$D/$t.json"
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python3 -c "import json,sys; print(sys.argv[1], len(json.load(open(sys.argv[2]))))" "$t" "$D/$t.json"
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done
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python3 - "$D" <<'PY'
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import hashlib, json, pathlib, sys
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d = pathlib.Path(sys.argv[1])
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log = json.loads((d / "change_log.json").read_text())
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ver = max(e["date"] for e in log if e.get("date"))
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files = {p.name: hashlib.sha256(p.read_bytes()).hexdigest() for p in sorted(d.glob("*.json")) if p.name != "source.json"}
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(d / "source.json").write_text(json.dumps({"name": "CPIC", "version": ver, "retrieved": d.name.split("-")[1],
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"url": "https://api.cpicpgx.org/v1", "license": "CC0-1.0",
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"files": files}, indent=1))
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print("CPIC data version", ver)
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PY
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@@ -810,6 +810,34 @@ pgx_cn_app = typer.Typer(help="Targeted PGx copy number (PCN-001).")
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pgx_app.add_typer(pgx_cn_app, name="copy-number")
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pgx_app.add_typer(pgx_cn_app, name="copy-number")
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pgx_db_app = typer.Typer(help="PGx allele-definition database (PGX-001).")
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pgx_app.add_typer(pgx_db_app, name="db")
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@pgx_db_app.command("build")
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def pgx_db_build_cmd(
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sources: Annotated[Path, typer.Option("--sources", help="Folder from scripts/pgx/fetch_sources.sh (required).")],
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fasta: Annotated[Path, typer.Option("--fasta", help="GRCh38 FASTA for variant normalisation (required).")],
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out: Annotated[Path, typer.Option("--out", help="Output folder for pgx_db-<schema>-<sha12>.sqlite.")] = Path("."),
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manifests: Annotated[
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list[Path] | None, typer.Option("--manifests", help="BPM manifest(s) for the probe map (repeatable).")
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] = None,
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csv: Annotated[list[Path] | None, typer.Option("--csv", help="CSV manifest(s), same order (indels).")] = None,
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mask: Annotated[list[Path] | None, typer.Option("--mask", help="Probe mask TSV(s) (PGX-010).")] = None,
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force: ForceOpt = False,
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log_json: LogJson = False,
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debug: Debug = False,
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quiet: Quiet = False,
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) -> None:
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"""Build the PGx DB from public sources (CLI-035, PGX-002)."""
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from simurg.pipeline.pgx_db import PgxDbOptions, run_db_build
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rep = _reporter("pgx db build", out, log_json, debug, quiet)
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o = PgxDbOptions(sources=sources, fasta=fasta, out=out, manifests=manifests or [], csvs=csv or [],
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masks=mask or [], force=force) # fmt: skip
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run_guarded(rep, lambda: run_db_build(o, rep))
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@pgx_cn_app.command("train")
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@pgx_cn_app.command("train")
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def pgx_cn_train_cmd(
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def pgx_cn_train_cmd(
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gtcs: Annotated[Path, typer.Option("--gtcs", help="Folder searched recursively for training GTCs (required).")],
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gtcs: Annotated[Path, typer.Option("--gtcs", help="Folder searched recursively for training GTCs (required).")],
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@@ -171,6 +171,7 @@ CATALOGUE: dict[str, MessageDef] = dict(
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_m("W_PGX_NO_ALT_CONTIG", "warning", "FASTA lacks a contig carrying a PGx region; REF written as N", "IN-062"),
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_m("W_PGX_NO_ALT_CONTIG", "warning", "FASTA lacks a contig carrying a PGx region; REF written as N", "IN-062"),
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_m("W_PGX_BATCH_COMPOSITION", "warning", "Batch spans several lots/batches or > 14 days of scans", "PCN-006"),
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_m("W_PGX_BATCH_COMPOSITION", "warning", "Batch spans several lots/batches or > 14 days of scans", "PCN-006"),
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_m("E_PGX_CN_FAILED", "error", "PGx CN calling failed for the sample", "PCN-002"),
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_m("E_PGX_CN_FAILED", "error", "PGx CN calling failed for the sample", "PCN-002"),
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_m("E_PGX_SOURCE", "error", "PGx source tables missing; run scripts/pgx/fetch_sources.sh", "PGX-001"),
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# --- methylation control QC (MET-001 .. MET-018) -------------------------------------------------
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# --- methylation control QC (MET-001 .. MET-018) -------------------------------------------------
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_m("E_METH_NO_ASSAY", "error", "Probe section not found", "MET-002"),
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_m("E_METH_NO_ASSAY", "error", "Probe section not found", "MET-002"),
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_m("E_METH_NO_CONTROLS", "error", "Missing control probes in manifest", "MET-002"),
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_m("E_METH_NO_CONTROLS", "error", "Missing control probes in manifest", "MET-002"),
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@@ -0,0 +1,223 @@
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"""PGx allele definitions from public sources → normalised VCF-style variants — spec PGX-001 … PGX-005.
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Pure functions: the reference sequence comes in as a ``fetch(contig, start0, end0)`` callable.
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CPIC tables (CC0, https://api.cpicpgx.org) [DB: CPIC allele definition, allele function, diplotype→phenotype]:
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``sequence_location`` gives each defining position as HGVS on the chromosome (``g.``/``m.``); ``allele_location_value``
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gives each allele's value there. Values are literal sequences (``A``, ``AA`` for a dup, ``TA(7)`` for a repeat) or
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``del…``/``ins…`` forms; the reference allele definition carries the reference value. Every value becomes a
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replacement of a reference window, then a left-normalised, anchored VCF (POS, REF, ALT) — the representation the
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SNV VCFs use (IN-046), so definitions and array records compare directly.
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"""
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from __future__ import annotations
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import re
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from collections.abc import Callable
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from dataclasses import dataclass, field
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from typing import Any
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Fetch = Callable[[str, int, int], str]
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HGVS_RE = re.compile(r"^([gm])\.(\d+)(?:_(\d+))?(.*)$")
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REPEAT_RE = re.compile(r"^([ACGT]+)\((\d+)\)$")
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IUPAC_WILDCARD = set("RYSWKMBDHVN") # CPIC core-allele definitions: the position does not constrain the allele
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@dataclass(frozen=True)
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class Window:
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"""Reference interval [start, end] (1-based, inclusive) replaced by allele values; ``insertion`` windows are the
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single anchor base S of ``g.S_EinsX`` (values are anchor + inserted sequence)."""
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start: int
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end: int
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kind: str # snv | del | ins | dup | repeat | delins
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unit: str = "" # repeat unit
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def parse_location(hgvs: str) -> Window | None:
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"""First HGVS expression of a CPIC ``chromosomelocation`` (several are ``;``-joined for one site)."""
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first = hgvs.split(";")[0].strip()
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m = HGVS_RE.match(first)
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if not m:
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return None
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s = int(m.group(2))
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e = int(m.group(3)) if m.group(3) else s
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rest = m.group(4)
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if re.fullmatch(r"[ACGT]>[ACGT]", rest):
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return Window(s, s, "snv")
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if rest.startswith("delins"):
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return Window(s, e, "delins")
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if rest.startswith("del"):
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return Window(s, e, "del")
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if rest.startswith("ins"):
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return Window(s, s, "ins")
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if rest.startswith("dup"):
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return Window(s, e, "dup")
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rm = re.fullmatch(r"([ACGT]+)\[(\d+)\]", rest)
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if rm:
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return Window(s, s, "repeat", rm.group(1))
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return None
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def value_sequence(value: str, w: Window, fetch: Fetch, contig: str) -> tuple[int, int, str] | None:
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"""(start, end, sequence) that the value puts in place of the reference window; None = unusable/ambiguous."""
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v = value.strip()
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if " or " in v or ";" in v or not v:
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return None
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if w.kind == "repeat":
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m = REPEAT_RE.match(v)
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unit = w.unit
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n_ref = 0
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while fetch(contig, w.start - 1 + n_ref * len(unit), w.start - 1 + (n_ref + 1) * len(unit)) == unit:
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n_ref += 1
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end = w.start - 1 + n_ref * len(unit)
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if m:
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return w.start, end, m.group(1) * int(m.group(2))
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if re.fullmatch(r"[ACGT]+", v):
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return w.start, end, v
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return None
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if w.kind == "ins":
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anchor = fetch(contig, w.start - 1, w.start)
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if v == "del":
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return w.start, w.start, anchor
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if v.startswith("ins"):
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return w.start, w.start, anchor + v[3:]
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return None
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if w.kind == "delins":
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if v.startswith("del"):
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return w.start, w.end, fetch(contig, w.start - 1, w.end)
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if v.startswith("ins"):
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return w.start, w.end, v[3:]
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return None
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if v.startswith("del"):
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return w.start, w.end, ""
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if re.fullmatch(r"[ACGT]+", v):
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return w.start, w.end, v
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return None
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def normalize(fetch: Fetch, contig: str, start: int, end: int, alt: str) -> tuple[int, str, str]:
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"""Replacement of reference [start, end] (1-based; end = start − 1 for a pure insertion before start) by ``alt``
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→ left-normalised, anchored (POS, REF, ALT) [LIT: Tan et al. 2015 Bioinformatics 31:2202 (vt normalize)]."""
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ref = fetch(contig, start - 1, end)
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pos = start
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# trim the common suffix, then the common prefix
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while ref and alt and ref[-1] == alt[-1]:
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ref, alt = ref[:-1], alt[:-1]
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while len(ref) > 0 and len(alt) > 0 and ref[0] == alt[0]:
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ref, alt = ref[1:], alt[1:]
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pos += 1
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if ref and alt and len(ref) == len(alt):
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return pos, ref, alt # SNV / MNV
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# left shift the indel while the base before it equals its last base
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while pos > 1 and (ref or alt):
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prev = fetch(contig, pos - 2, pos - 1)
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body = ref or alt
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if prev != body[-1] or (ref and alt):
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break
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if ref:
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ref = prev + ref[:-1]
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else:
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alt = prev + alt[:-1]
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pos -= 1
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anchor = fetch(contig, pos - 2, pos - 1)
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return pos - 1, anchor + ref, anchor + alt
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@dataclass
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class VariantSite:
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location_id: int
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gene: str
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chrom: str # contig name as in the FASTA
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hgvs: str
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rsid: str | None
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ref_value: str | None
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alleles: dict[str, tuple[int, str, str]] = field(default_factory=dict) # value → normalised (pos, ref, alt)
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@dataclass
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class AlleleDef:
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gene: str
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name: str
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function: str | None
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activity: str | None
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reference: bool
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structural: bool
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variants: list[tuple[int, str]] = field(default_factory=list) # (location_id, value) where ≠ reference
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frequencies: dict[str, float] = field(default_factory=dict)
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wildcards: list[int] = field(default_factory=list) # location ids with an IUPAC value (either base)
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@property
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def undefined(self) -> bool:
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"""A non-reference allele without any defining variant cannot be called (e.g. CPIC NUDT15 *2)."""
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return not self.reference and not self.variants
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def cpic_definitions(
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t: dict[str, list[dict[str, Any]]], fetch: Fetch, contig_of: Callable[[str], str | None]
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) -> tuple[dict[str, list[AlleleDef]], dict[int, VariantSite], list[str]]:
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"""CPIC tables → (gene → allele definitions, location id → site, problems)."""
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problems: list[str] = []
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gene_chr = {g["symbol"]: g.get("chr") for g in t["gene"]}
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|
locs = {loc["id"]: loc for loc in t["sequence_location"]}
|
||||||
|
values: dict[int, list[tuple[int, str]]] = {}
|
||||||
|
for v in t["allele_location_value"]:
|
||||||
|
values.setdefault(v["alleledefinitionid"], []).append((v["locationid"], v["variantallele"]))
|
||||||
|
func = {(a["genesymbol"], a["name"]): a for a in t["allele"]}
|
||||||
|
defs: dict[str, list[AlleleDef]] = {}
|
||||||
|
sites: dict[int, VariantSite] = {}
|
||||||
|
ref_value: dict[int, str] = {}
|
||||||
|
for d in sorted(t["allele_definition"], key=lambda d: (d["genesymbol"], d["name"])):
|
||||||
|
if d.get("matchesreferencesequence"):
|
||||||
|
for lid, val in values.get(d["id"], []):
|
||||||
|
ref_value[lid] = val
|
||||||
|
for d in sorted(t["allele_definition"], key=lambda d: (d["genesymbol"], d["name"])):
|
||||||
|
g = d["genesymbol"]
|
||||||
|
a = func.get((g, d["name"]), {})
|
||||||
|
freq = {k: float(v) for k, v in (a.get("frequency") or {}).items() if isinstance(v, int | float)}
|
||||||
|
ref_def, sv = bool(d.get("matchesreferencesequence")), bool(d.get("structuralvariation"))
|
||||||
|
ad = AlleleDef(g, d["name"], a.get("clinicalfunctionalstatus"), a.get("activityvalue"), ref_def, sv, [], freq)
|
||||||
|
for lid, val in sorted(values.get(d["id"], [])):
|
||||||
|
loc = locs.get(lid)
|
||||||
|
if loc is None:
|
||||||
|
continue
|
||||||
|
if lid not in sites:
|
||||||
|
hg = loc.get("chromosomelocation") or ""
|
||||||
|
chrom = "chrM" if hg.startswith("m.") else (gene_chr.get(g) or "")
|
||||||
|
contig = contig_of(chrom) if chrom else None
|
||||||
|
if contig is None:
|
||||||
|
problems.append(f"{g} {loc['name']}: no contig for {chrom!r}")
|
||||||
|
continue
|
||||||
|
sites[lid] = VariantSite(lid, g, contig, hg, loc.get("dbsnpid"), ref_value.get(lid))
|
||||||
|
site = sites[lid]
|
||||||
|
if len(val) == 1 and val in IUPAC_WILDCARD:
|
||||||
|
ad.wildcards.append(lid)
|
||||||
|
elif val != site.ref_value:
|
||||||
|
ad.variants.append((lid, val))
|
||||||
|
defs.setdefault(g, []).append(ad)
|
||||||
|
for lid, site in sites.items():
|
||||||
|
w = parse_location(site.hgvs)
|
||||||
|
if w is None:
|
||||||
|
problems.append(f"{site.gene} {site.hgvs}: unparsed location")
|
||||||
|
continue
|
||||||
|
vals = {val for d in defs.get(site.gene, []) for (l2, val) in d.variants if l2 == lid}
|
||||||
|
for val in sorted(vals):
|
||||||
|
seq = value_sequence(val, w, fetch, site.chrom)
|
||||||
|
if seq is None:
|
||||||
|
problems.append(f"{site.gene} {site.hgvs}: value {val!r} not representable")
|
||||||
|
continue
|
||||||
|
s, e, alt = seq
|
||||||
|
if w.kind == "ins":
|
||||||
|
s, e, alt = s + 1, s, alt[1:]
|
||||||
|
site.alleles[val] = normalize(fetch, site.chrom, s, e, alt)
|
||||||
|
return defs, sites, problems
|
||||||
|
|
||||||
|
|
||||||
|
def result_basis(gene: str, names: list[str]) -> str:
|
||||||
|
"""PGX-002 ``genes.result_basis``."""
|
||||||
|
if gene in ("HLA-A", "HLA-B"):
|
||||||
|
return "tagging_variant"
|
||||||
|
if gene in ("G6PD", "APOE"):
|
||||||
|
return "haplotype_named"
|
||||||
|
if names and all(n.startswith("*") for n in names):
|
||||||
|
return "star_allele"
|
||||||
|
return "variant_based"
|
||||||
@@ -0,0 +1,223 @@
|
|||||||
|
"""``simurg pgx db build`` — the PGx allele-definition database (spec PGX-001 … PGX-005, PGX-010, IN-053, CLI-035).
|
||||||
|
|
||||||
|
I/O and orchestration; the parsing and normalisation live in ``simurg.pgx.db``. Sources are the dated folders written
|
||||||
|
by ``scripts/pgx/fetch_sources.sh`` (``cpic-YYYYMMDD/`` with ``source.json``). The build is deterministic: rows are
|
||||||
|
inserted in sorted order into a fresh SQLite file with fixed pragmas, and the file is named by its content hash.
|
||||||
|
"""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import hashlib
|
||||||
|
import json
|
||||||
|
import sqlite3
|
||||||
|
from dataclasses import dataclass, field
|
||||||
|
from pathlib import Path
|
||||||
|
from typing import Any
|
||||||
|
|
||||||
|
from simurg import __version__
|
||||||
|
from simurg.core.errors import ExitCode, SimurgError
|
||||||
|
from simurg.core.log import Reporter
|
||||||
|
|
||||||
|
DB_SCHEMA = 1
|
||||||
|
CPIC_TABLES = ("gene", "allele", "allele_definition", "allele_location_value", "sequence_location", "gene_result",
|
||||||
|
"gene_result_lookup") # fmt: skip
|
||||||
|
GENE_PAD = 50_000 # probes within this distance of a gene's defining positions are resolved for probe_map
|
||||||
|
|
||||||
|
SCHEMA_SQL = """
|
||||||
|
CREATE TABLE meta(key TEXT PRIMARY KEY, value TEXT NOT NULL);
|
||||||
|
CREATE TABLE genes(gene TEXT PRIMARY KEY, result_basis TEXT NOT NULL, chrom TEXT);
|
||||||
|
CREATE TABLE alleles(gene TEXT, allele TEXT, kind TEXT, function TEXT, activity TEXT, structural INTEGER,
|
||||||
|
defined INTEGER, PRIMARY KEY(gene, allele));
|
||||||
|
CREATE TABLE allele_variants(gene TEXT, allele TEXT, build TEXT, chrom TEXT, pos INTEGER, ref TEXT, alt TEXT,
|
||||||
|
hgvs TEXT, rsid TEXT, location_id INTEGER, value TEXT);
|
||||||
|
CREATE TABLE allele_wildcards(gene TEXT, allele TEXT, location_id INTEGER);
|
||||||
|
CREATE TABLE sites(gene TEXT, location_id INTEGER, chrom TEXT, hgvs TEXT, rsid TEXT, ref_value TEXT,
|
||||||
|
PRIMARY KEY(gene, location_id));
|
||||||
|
CREATE TABLE site_values(gene TEXT, location_id INTEGER, value TEXT, pos INTEGER, ref TEXT, alt TEXT);
|
||||||
|
CREATE TABLE probe_map(manifest TEXT, probe_name TEXT, chrom TEXT, pos INTEGER, ref TEXT, alt TEXT);
|
||||||
|
CREATE TABLE masks(manifest TEXT, probe_name TEXT, reason TEXT);
|
||||||
|
CREATE TABLE limitations(manifest TEXT, gene TEXT, allele TEXT, status TEXT, reported_as TEXT);
|
||||||
|
CREATE TABLE frequencies(gene TEXT, allele TEXT, population TEXT, freq REAL);
|
||||||
|
CREATE TABLE phenotypes(guideline TEXT, gene TEXT, lookup_key TEXT, activity_score TEXT, phenotype TEXT);
|
||||||
|
CREATE INDEX av_pos ON allele_variants(chrom, pos);
|
||||||
|
CREATE INDEX pm_pos ON probe_map(manifest, chrom, pos);
|
||||||
|
"""
|
||||||
|
|
||||||
|
|
||||||
|
@dataclass
|
||||||
|
class PgxDbOptions:
|
||||||
|
sources: Path
|
||||||
|
fasta: Path
|
||||||
|
out: Path
|
||||||
|
manifests: list[Path] = field(default_factory=list)
|
||||||
|
csvs: list[Path] = field(default_factory=list)
|
||||||
|
masks: list[Path] = field(default_factory=list)
|
||||||
|
force: bool = False
|
||||||
|
|
||||||
|
|
||||||
|
def _latest(sources: Path, prefix: str) -> Path | None:
|
||||||
|
cands = sorted(p for p in sources.glob(f"{prefix}-*") if (p / "source.json").exists())
|
||||||
|
return cands[-1] if cands else None
|
||||||
|
|
||||||
|
|
||||||
|
def _load_cpic(d: Path) -> dict[str, list[dict[str, Any]]]:
|
||||||
|
t = {}
|
||||||
|
for name in CPIC_TABLES:
|
||||||
|
p = d / f"{name}.json"
|
||||||
|
if not p.exists():
|
||||||
|
raise SimurgError("E_PGX_SOURCE", f"{p} missing", hint="run scripts/pgx/fetch_sources.sh")
|
||||||
|
t[name] = json.loads(p.read_text(encoding="utf-8"))
|
||||||
|
return t
|
||||||
|
|
||||||
|
|
||||||
|
def _probe_sites(
|
||||||
|
bpm_path: Path,
|
||||||
|
csv_path: Path | None,
|
||||||
|
genome: Any,
|
||||||
|
cmap: Any,
|
||||||
|
windows: dict[str, list[tuple[int, int]]],
|
||||||
|
rep: Reporter,
|
||||||
|
) -> list[Any]:
|
||||||
|
"""Plus-strand, normalised sites of the manifest probes inside the gene windows (the SNV VCF representation)."""
|
||||||
|
from simurg.formats.bpm import read_bpm
|
||||||
|
from simurg.harmonize.sites import ManifestView, map_locus
|
||||||
|
|
||||||
|
bpm = read_bpm(bpm_path)
|
||||||
|
csvm = None
|
||||||
|
if csv_path is not None:
|
||||||
|
from simurg.formats.csv_manifest import read_csv_manifest
|
||||||
|
|
||||||
|
csvm = read_csv_manifest(csv_path)
|
||||||
|
elif any("D" in s for s in bpm.snps):
|
||||||
|
rep.warn("W_SKIP_INDEL_CONTEXT", f"{bpm_path.name}: no CSV manifest, indel probes are not mapped")
|
||||||
|
src = csvm or bpm
|
||||||
|
mv = ManifestView(bpm.names, bpm.snps, bpm.chroms, bpm.map_infos.tolist(), src.ilmn_strands, src.source_strands,
|
||||||
|
src.ref_strands if any(src.ref_strands) else bpm.ref_strands,
|
||||||
|
csvm.source_seqs if csvm else [""] * bpm.num_loci, bpm.assay_types.tolist(),
|
||||||
|
bpm.intensity_only.tolist()) # fmt: skip
|
||||||
|
out = []
|
||||||
|
for i in range(bpm.num_loci):
|
||||||
|
c = cmap.get(bpm.chroms[i])
|
||||||
|
if c is None or c not in windows:
|
||||||
|
continue
|
||||||
|
p = int(bpm.map_infos[i])
|
||||||
|
if not any(a - GENE_PAD <= p <= b + GENE_PAD for a, b in windows[c]):
|
||||||
|
continue
|
||||||
|
site, _ = map_locus(i, mv, genome.fetch, cmap.get, genome.build or "GRCh38")
|
||||||
|
if site is not None:
|
||||||
|
out.append(site)
|
||||||
|
return out
|
||||||
|
|
||||||
|
|
||||||
|
def run_db_build(o: PgxDbOptions, rep: Reporter) -> int:
|
||||||
|
"""``simurg pgx db build`` (CLI-035)."""
|
||||||
|
from simurg.formats.bpm import read_bpm
|
||||||
|
from simurg.formats.fasta import ContigMap, Genome
|
||||||
|
from simurg.pgx.db import cpic_definitions, result_basis
|
||||||
|
|
||||||
|
cdir = _latest(o.sources, "cpic")
|
||||||
|
if cdir is None:
|
||||||
|
raise SimurgError("E_PGX_SOURCE", f"no cpic-YYYYMMDD source folder in {o.sources}",
|
||||||
|
hint="run scripts/pgx/fetch_sources.sh") # fmt: skip
|
||||||
|
csrc = json.loads((cdir / "source.json").read_text())
|
||||||
|
genome = Genome(o.fasta)
|
||||||
|
if genome.build not in ("GRCh38", "unknown", ""):
|
||||||
|
raise SimurgError("E_BUILD_MISMATCH", f"the PGx DB is GRCh38 only (FASTA is {genome.build})") # PCN-015
|
||||||
|
cmap = ContigMap([e.name for e in genome.entries], "auto")
|
||||||
|
t = _load_cpic(cdir)
|
||||||
|
defs, sites, problems = cpic_definitions(t, genome.fetch, cmap.get)
|
||||||
|
for p in problems:
|
||||||
|
rep.info(f"definition note: {p}")
|
||||||
|
rows: dict[str, list[tuple[Any, ...]]] = {k: [] for k in ("genes", "alleles", "allele_variants", "allele_wildcards",
|
||||||
|
"sites", "site_values", "frequencies", "phenotypes",
|
||||||
|
"probe_map", "masks")} # fmt: skip
|
||||||
|
gene_chr = {g["symbol"]: g.get("chr") for g in t["gene"]}
|
||||||
|
for gene, ds in sorted(defs.items()):
|
||||||
|
rows["genes"].append((gene, result_basis(gene, [d.name for d in ds]), gene_chr.get(gene)))
|
||||||
|
for d in ds:
|
||||||
|
kind = "reference" if d.reference else ("star_allele" if d.name.startswith("*") else "named_haplotype")
|
||||||
|
rows["alleles"].append(
|
||||||
|
(gene, d.name, kind, d.function, d.activity, int(d.structural), int(not d.undefined))
|
||||||
|
)
|
||||||
|
for lid, val in d.variants:
|
||||||
|
s = sites.get(lid)
|
||||||
|
if s is None or val not in s.alleles:
|
||||||
|
continue
|
||||||
|
pos, ref, alt = s.alleles[val]
|
||||||
|
rows["allele_variants"].append(
|
||||||
|
(gene, d.name, "GRCh38", s.chrom, pos, ref, alt, s.hgvs, s.rsid, lid, val)
|
||||||
|
)
|
||||||
|
for lid in d.wildcards:
|
||||||
|
rows["allele_wildcards"].append((gene, d.name, lid))
|
||||||
|
for pop, f in sorted(d.frequencies.items()):
|
||||||
|
rows["frequencies"].append((gene, d.name, pop, f))
|
||||||
|
for lid, s in sorted(sites.items()):
|
||||||
|
rows["sites"].append((s.gene, lid, s.chrom, s.hgvs, s.rsid, s.ref_value))
|
||||||
|
for val, (pos, ref, alt) in sorted(s.alleles.items()):
|
||||||
|
rows["site_values"].append((s.gene, lid, val, pos, ref, alt))
|
||||||
|
results = {r["id"]: r for r in t["gene_result"]}
|
||||||
|
for lk in t["gene_result_lookup"]:
|
||||||
|
res = results.get(lk["phenotypeid"])
|
||||||
|
if res is None:
|
||||||
|
continue
|
||||||
|
key = json.dumps(lk.get("lookupkey"), sort_keys=True, ensure_ascii=False)
|
||||||
|
rows["phenotypes"].append(("cpic", res["genesymbol"], key, lk.get("totalactivityscore"), res["result"]))
|
||||||
|
# probe map (PGX-003): manifest probes whose normalised site carries a DB variant
|
||||||
|
windows: dict[str, list[tuple[int, int]]] = {}
|
||||||
|
for av in rows["allele_variants"]:
|
||||||
|
windows.setdefault(av[3], []).append((av[4], av[4] + len(av[5])))
|
||||||
|
var_keys = {(av[3], av[4], av[5], av[6]) for av in rows["allele_variants"]}
|
||||||
|
manifests = []
|
||||||
|
csvs = dict(zip(o.manifests, o.csvs, strict=False))
|
||||||
|
for bpm_path in o.manifests:
|
||||||
|
name = read_bpm(bpm_path).manifest_name
|
||||||
|
manifests.append(name)
|
||||||
|
n = 0
|
||||||
|
for ps in _probe_sites(bpm_path, csvs.get(bpm_path), genome, cmap, windows, rep):
|
||||||
|
for alt in ps.alleles:
|
||||||
|
if alt != ps.ref and (ps.contig, ps.pos, ps.ref, alt) in var_keys:
|
||||||
|
rows["probe_map"].append((name, ps.name, ps.contig, ps.pos, ps.ref, alt))
|
||||||
|
n += 1
|
||||||
|
rep.info(f"{name}: {n} probe-to-variant link(s)")
|
||||||
|
for mp in o.masks:
|
||||||
|
for ln in mp.read_text(encoding="utf-8").splitlines():
|
||||||
|
if ln.strip() and not ln.startswith("#"):
|
||||||
|
cols = ln.split("\t")
|
||||||
|
rows["masks"].append((cols[2] if len(cols) > 2 else mp.stem, cols[0], cols[1] if len(cols) > 1 else ""))
|
||||||
|
meta = {"schema": "simurg.pgx_db", "schema_version": str(DB_SCHEMA), "builder": f"SimurgArray {__version__}",
|
||||||
|
"genome_build": "GRCh38", "fasta_sha256": genome.sha256, "sqlite_version": sqlite3.sqlite_version,
|
||||||
|
"allele_sources": json.dumps([{"name": "CPIC", "version": csrc["version"], "retrieved": csrc["retrieved"],
|
||||||
|
"license": csrc.get("license")}]),
|
||||||
|
"phenotype_sources": json.dumps([{"name": "CPIC", "version": csrc["version"]}]),
|
||||||
|
"cpic_files_sha256": json.dumps(csrc.get("files", {}), sort_keys=True),
|
||||||
|
"manifests": json.dumps(sorted(manifests)), "definition_notes": json.dumps(problems)} # fmt: skip
|
||||||
|
# content hash over the sorted rows and meta (IN-053: the name and meta carry it; a file cannot hold its own hash)
|
||||||
|
for rs in rows.values():
|
||||||
|
rs.sort(key=lambda r: tuple(str(x) for x in r))
|
||||||
|
sha = hashlib.sha256(json.dumps({"rows": rows, "meta": sorted(meta.items())}, sort_keys=True,
|
||||||
|
default=str).encode()).hexdigest() # fmt: skip
|
||||||
|
meta["content_sha256"] = sha
|
||||||
|
o.out.mkdir(parents=True, exist_ok=True)
|
||||||
|
tmp = o.out / ".pgx_db.part.sqlite"
|
||||||
|
tmp.unlink(missing_ok=True)
|
||||||
|
con = sqlite3.connect(tmp)
|
||||||
|
con.execute("PRAGMA page_size=4096")
|
||||||
|
con.execute("PRAGMA journal_mode=OFF")
|
||||||
|
con.executescript(SCHEMA_SQL)
|
||||||
|
for table, rs in rows.items():
|
||||||
|
if rs:
|
||||||
|
ph = ",".join("?" * len(rs[0]))
|
||||||
|
con.executemany(f"INSERT INTO {table} VALUES ({ph})", rs)
|
||||||
|
con.executemany("INSERT INTO meta VALUES (?, ?)", sorted(meta.items()))
|
||||||
|
con.commit()
|
||||||
|
con.execute("VACUUM")
|
||||||
|
con.close()
|
||||||
|
final = o.out / f"pgx_db-{DB_SCHEMA}-{sha[:12]}.sqlite"
|
||||||
|
if final.exists() and not o.force:
|
||||||
|
tmp.unlink()
|
||||||
|
rep.info(f"identical PGx DB already present: {final}")
|
||||||
|
return ExitCode.OK
|
||||||
|
tmp.replace(final)
|
||||||
|
rep.info(f"PGx DB: {len(defs)} genes, {len(rows['alleles'])} alleles, {len(rows['allele_variants'])} variant "
|
||||||
|
f"rows, {len(rows['probe_map'])} probe links → {final} (content sha256 {sha})") # fmt: skip
|
||||||
|
return ExitCode.OK
|
||||||
@@ -0,0 +1,123 @@
|
|||||||
|
"""PGx DB build (spec PGX-001 … PGX-005, IN-053, CLI-035)."""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import json
|
||||||
|
import sqlite3
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
from typer.testing import CliRunner
|
||||||
|
|
||||||
|
from simurg.cli.main import app
|
||||||
|
from simurg.pgx.db import Window, cpic_definitions, normalize, parse_location, value_sequence
|
||||||
|
|
||||||
|
SEQ = "ACGTACGTTTTTAGAGAGAGCCCGGGTATATATAGGCCAATTGGCCAA" * 3
|
||||||
|
|
||||||
|
|
||||||
|
def fetch(contig: str, s0: int, e0: int) -> str:
|
||||||
|
return SEQ[s0:e0]
|
||||||
|
|
||||||
|
|
||||||
|
def test_parse_location() -> None:
|
||||||
|
assert parse_location("g.5C>T") == Window(5, 5, "snv")
|
||||||
|
assert parse_location("g.9_12del") == Window(9, 12, "del")
|
||||||
|
assert parse_location("g.13_14insGA") == Window(13, 13, "ins")
|
||||||
|
assert parse_location("g.20dup") == Window(20, 20, "dup")
|
||||||
|
assert parse_location("g.13AG[4]") == Window(13, 13, "repeat", "AG")
|
||||||
|
assert parse_location("g.21_22delinsTT") == Window(21, 22, "delins")
|
||||||
|
assert parse_location("m.961delT; m.961delTinsC(n)") == Window(961, 961, "del")
|
||||||
|
|
||||||
|
|
||||||
|
def test_normalize_left_aligns() -> None: # the SNV VCF representation (IN-046)
|
||||||
|
# deleting one T of TTTTT (positions 8-12) → anchored at the base before the run
|
||||||
|
assert normalize(fetch, "1", 11, 11, "") == (7, "GT", "G")
|
||||||
|
# inserting AG into AGAGAGAG (13-20) → left-most position
|
||||||
|
assert normalize(fetch, "1", 21, 20, "AG") == (12, "T", "TAG")
|
||||||
|
assert normalize(fetch, "1", 5, 5, "G") == (5, "A", "G")
|
||||||
|
w = parse_location("g.13AG[4]")
|
||||||
|
assert w is not None
|
||||||
|
s, e, alt = value_sequence("AG(5)", w, fetch, "1") or (0, 0, "")
|
||||||
|
assert (s, e) == (13, 20) and normalize(fetch, "1", s, e, alt) == (12, "T", "TAG")
|
||||||
|
assert value_sequence("AG(3) or AG(4)", w, fetch, "1") is None # ambiguous CPIC value
|
||||||
|
|
||||||
|
|
||||||
|
def _tables() -> dict[str, list[dict]]:
|
||||||
|
loc = [
|
||||||
|
{"id": 1, "name": "5A>G", "chromosomelocation": "g.5A>G", "genesymbol": "GENE1", "dbsnpid": "rs1"},
|
||||||
|
{"id": 2, "name": "11delT", "chromosomelocation": "g.11del", "genesymbol": "GENE1", "dbsnpid": "rs2"},
|
||||||
|
{"id": 3, "name": "30C>T", "chromosomelocation": "g.30G>T", "genesymbol": "GENE1", "dbsnpid": "rs3"},
|
||||||
|
]
|
||||||
|
defs = [
|
||||||
|
{"id": 10, "genesymbol": "GENE1", "name": "*1", "matchesreferencesequence": True, "structuralvariation": False},
|
||||||
|
{
|
||||||
|
"id": 11,
|
||||||
|
"genesymbol": "GENE1",
|
||||||
|
"name": "*2",
|
||||||
|
"matchesreferencesequence": False,
|
||||||
|
"structuralvariation": False,
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"id": 12,
|
||||||
|
"genesymbol": "GENE1",
|
||||||
|
"name": "*3",
|
||||||
|
"matchesreferencesequence": False,
|
||||||
|
"structuralvariation": False,
|
||||||
|
},
|
||||||
|
{"id": 13, "genesymbol": "GENE1", "name": "*5", "matchesreferencesequence": False, "structuralvariation": True},
|
||||||
|
]
|
||||||
|
alv = [
|
||||||
|
{"alleledefinitionid": 10, "locationid": 1, "variantallele": "A"},
|
||||||
|
{"alleledefinitionid": 10, "locationid": 2, "variantallele": "T"},
|
||||||
|
{"alleledefinitionid": 10, "locationid": 3, "variantallele": "G"},
|
||||||
|
{"alleledefinitionid": 11, "locationid": 1, "variantallele": "G"},
|
||||||
|
{"alleledefinitionid": 11, "locationid": 3, "variantallele": "K"}, # IUPAC: not constraining
|
||||||
|
{"alleledefinitionid": 12, "locationid": 2, "variantallele": "delT"},
|
||||||
|
]
|
||||||
|
allele = [
|
||||||
|
{"genesymbol": "GENE1", "name": "*1", "clinicalfunctionalstatus": "Normal function", "activityvalue": "1.0",
|
||||||
|
"frequency": {"European": 0.7}},
|
||||||
|
{"genesymbol": "GENE1", "name": "*2", "clinicalfunctionalstatus": "No function", "activityvalue": "0.0",
|
||||||
|
"frequency": {"European": 0.2}},
|
||||||
|
{"genesymbol": "GENE1", "name": "*3", "clinicalfunctionalstatus": "Decreased function", "activityvalue": "0.5",
|
||||||
|
"frequency": None},
|
||||||
|
] # fmt: skip
|
||||||
|
return {"gene": [{"symbol": "GENE1", "chr": "chr1"}], "sequence_location": loc, "allele_definition": defs,
|
||||||
|
"allele_location_value": alv, "allele": allele,
|
||||||
|
"gene_result": [{"id": 50, "genesymbol": "GENE1", "result": "Poor Metabolizer"}],
|
||||||
|
"gene_result_lookup": [{"phenotypeid": 50, "lookupkey": {"No function": 2}, "totalactivityscore": "0.0"}]} # fmt: skip
|
||||||
|
|
||||||
|
|
||||||
|
def test_cpic_definitions() -> None: # PGX-002: variants, wildcards, undefined structural alleles
|
||||||
|
defs, sites, problems = cpic_definitions(_tables(), fetch, lambda c: "1")
|
||||||
|
assert not problems
|
||||||
|
by = {d.name: d for d in defs["GENE1"]}
|
||||||
|
assert by["*1"].reference and not by["*1"].variants
|
||||||
|
assert [sites[lid].alleles[v] for lid, v in by["*2"].variants] == [(5, "A", "G")]
|
||||||
|
assert by["*2"].wildcards == [3]
|
||||||
|
assert [sites[lid].alleles[v] for lid, v in by["*3"].variants] == [(7, "GT", "G")]
|
||||||
|
assert by["*5"].undefined and by["*5"].structural
|
||||||
|
|
||||||
|
|
||||||
|
def test_db_build_deterministic(tmp_path: Path) -> None: # IN-053, CLI-035
|
||||||
|
src = tmp_path / "sources" / "cpic-20260101"
|
||||||
|
src.mkdir(parents=True)
|
||||||
|
for k, v in _tables().items():
|
||||||
|
(src / f"{k}.json").write_text(json.dumps(v))
|
||||||
|
(src / "source.json").write_text(json.dumps({"name": "CPIC", "version": "2026-01-01", "retrieved": "20260101"}))
|
||||||
|
fa = tmp_path / "g.fa"
|
||||||
|
fa.write_text(">chr1\n" + SEQ + "\n")
|
||||||
|
outs = []
|
||||||
|
for k in range(2):
|
||||||
|
out = tmp_path / f"db{k}"
|
||||||
|
r = CliRunner().invoke(app, ["pgx", "db", "build", "--sources", str(tmp_path / "sources"), "--fasta", str(fa),
|
||||||
|
"--out", str(out), "--quiet"]) # fmt: skip
|
||||||
|
assert r.exit_code == 0, r.output
|
||||||
|
outs.append(next(out.glob("pgx_db-1-*.sqlite")))
|
||||||
|
assert outs[0].name == outs[1].name and outs[0].read_bytes() == outs[1].read_bytes()
|
||||||
|
con = sqlite3.connect(outs[0])
|
||||||
|
assert con.execute("select result_basis from genes").fetchall() == [("star_allele",)]
|
||||||
|
assert con.execute("select allele, pos, ref, alt from allele_variants order by allele").fetchall() == [
|
||||||
|
("*2", 5, "A", "G"), ("*3", 7, "GT", "G")] # fmt: skip
|
||||||
|
meta = dict(con.execute("select key, value from meta").fetchall())
|
||||||
|
assert meta["content_sha256"][:12] in outs[0].name and json.loads(meta["allele_sources"])[0]["name"] == "CPIC"
|
||||||
|
assert con.execute("select phenotype from phenotypes").fetchone() == ("Poor Metabolizer",)
|
||||||
Reference in new issue
Block a user