PGx: ClinPGx variant-based genes (PGX-008) and --guideline dpwg (PGX-025)
- fetch_sources.sh downloads ClinPGx clinicalVariants (CC BY-SA 4.0); pgx db build adds genotype-only variant-based genes (levels 1A-2B, level 3 for the parity list), rsIDs resolved from the manifest's probes: 70 genes in the DB. - pgx phenotype --guideline dpwg: CPIC mappings for CPIC genes (as ClinPGx curates DPWG), no phenotype for DPWG-only genes (flags dpwg_via_cpic_mapping / dpwg_mapping_not_available). K-029 updated. Co-Authored-By: Claude Opus 5.5 <[email protected]> Claude-Session: https://claude.ai/code/session_01814GKVzZVL3FuF3DeiZXhv
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@@ -18,6 +18,7 @@ used only as external subprocess oracles and are not copied or linked.
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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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| [PharmVar](https://www.pharmvar.org) haplotype definitions (Gaedigk et al. 2018 CPT 103:399) | PharmVar terms of use (attribution) | per-gene zips downloaded by `scripts/pgx/fetch_sources.sh` into `data/` (never committed); `simurg pgx db build` derives core-allele definitions for genes CPIC does not define |
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| [GeT-RM](https://www.cdc.gov/lab-quality/php/get-rm/reference-materials.html) consolidated PGx/HLA table (CDC) | US government work | validation truth only (`scripts/pgx/getrm_truth.py`), not redistributed |
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| [ClinPGx](https://www.clinpgx.org) (formerly PharmGKB) clinical-annotation variants | CC BY-SA 4.0 (attribution: ClinPGx, https://www.clinpgx.org/page/citingClinpgx) | `clinicalVariants.zip` downloaded by `scripts/pgx/fetch_sources.sh` into `data/` (never committed); rsIDs become genotype-only variant-based genes in the local PGx DB |
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## BSD-2-Clause (BeadArrayFiles, verbatim from its README)
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@@ -4,7 +4,7 @@ Plan §20 lists the open questions; this file records what the implementation ha
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| ID | Date | Topic | Finding | Status |
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|---|---|---|---|---|
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| K-029 | 2026-09-29 | PGx star alleles (v2) | (1) PGX-012 error model: ε(GS) = 0.5·(1 − GS)² was replaced by ε = 1e-3 (GS ≥ 0.15) / 0.05 — after probe masking 0 of 9 740 GSA v4 PGx calls disagreed with 1000G 30x at any GS, and the old model made correct low-GS calls lose to the prior (spec amended). (2) PGX-010 masks derived from 14 individuals (spec: ≥ 100); a variant absent from the filtered 1000G panel counts as hom-ref only if rare (CYP2B6 rs2279343 is filtered out, not absent). (3) CPIC core-allele definitions use IUPAC wildcards; alleles without definitions (NUDT15 *2, structural CYP2D6) are not callable from SNVs. (4) GeT-RM uses legacy UGT1A1/SLCO1B1 names. Result vs GeT-RM (16 CEPH): 100/109 gene calls, CYP2D6/2C19/2C9 41/45. | Open: hybrids, G6PD/variant-based genes, PharmVar genes, phenotypes; larger/independent truth (`docs/validation/V2_pgx_star.md`). |
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| K-029 | 2026-09-29 | PGx star alleles (v2) | (1) PGX-012 error model: ε(GS) = 0.5·(1 − GS)² was replaced by ε = 1e-3 (GS ≥ 0.15) / 0.05 — after probe masking 0 of 9 740 GSA v4 PGx calls disagreed with 1000G 30x at any GS, and the old model made correct low-GS calls lose to the prior (spec amended). (2) PGX-010 masks derived from 14 individuals (spec: ≥ 100); a variant absent from the filtered 1000G panel counts as hom-ref only if rare (CYP2B6 rs2279343 is filtered out, not absent). (3) CPIC core-allele definitions use IUPAC wildcards; alleles without definitions (NUDT15 *2, structural CYP2D6) are not callable from SNVs. (4) GeT-RM uses legacy UGT1A1/SLCO1B1 names. Result vs GeT-RM (16 CEPH): 100/109 gene calls, CYP2D6/2C19/2C9 41/45. (5) DPWG: no public machine-readable genotype→phenotype mapping; CPIC mappings are used for genes CPIC covers (as ClinPGx does), DPWG-only genes (CYP1A2, CYP3A4, F5) get no phenotype. (6) GeT-RM definitions are older than CPIC/PharmVar for UGT1A1, SLCO1B1, CYP1A2 and CYP2C8 (e.g. PharmVar CYP2C8 *19 = rs2071426 alone). Result vs GeT-RM (16 CEPH, 21 genes): 154/168 comparable gene calls. | Open: larger/independent truth set; KNMP DPWG tables if they become available (`docs/validation/V2_pgx_star.md`). |
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| K-028 | 2026-09-29 | PGx CN (v2) | Deviations from PCN-009: the per-probe reference is the training cohort's median stored in the model (a calling-batch median is not CN 2 where deletions are common, e.g. GSTM1 null ≈ 50 %); no GC-correction step; the CN mixture is ours: µ_c = δ + γ·log2((c+1)/3) per region with a free lower CN-0 component and Hardy–Weinberg-constrained weights (probe compression differs by region: γ ≈ 0.19 CYP2D6.p5 … 0.56 GSTT1). Interim validation on the GSA v4 PGx demo — whose 36 arrays turned out to be 30 CEPH/1000G individuals — against NYGC 30x SV RD_CN: 224/240 region calls (GSTM1, UGT2B17 30/30), but in-sample (trained on the same arrays, < 96 samples, priors chosen with this truth in view). | Open: validate on an independent GSA-PGx cohort; CYP2D6 via GeT-RM star alleles (`docs/validation/V2_pgx_cn.md`). |
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| K-027 | 2026-09-29 | CN/LOH (v2) | CYTO-014 noise gate: the summary `logr_dev` also measures cluster-file mismatch (GSE165845: 0.246, all samples `SampleQuality`) while the LRR used after the batch reference has SD ≈ 0.1; the gate now uses the SD of the normalised LRR (the JSON still reports the summary value). Spec: built-in mask/cytobands from UCSC; the annotation bundle uses UCSC ncbiRefSeq instead of RefSeq GFF + Ensembl GTF + HGNC. Real-data result: constitutional DEL/DUP calls 74–77 % in NYGC truth, mosaic calls mostly false positives. Pi tuning: mosaic prior / switch distance barely matter; CYTO-041 (noise-normalised BAF split, complete-loss promotion) cuts PASS mosaic calls by ~30 % without losing implanted ≥ 15 % mosaics. Two limits remain: (1) without phasing, < 20 % mosaic losses are not separable from regional BAF noise; (2) common CNVs (carrier frequency > 20 %) are almost never detected (1/236 DEL) because the median-LRR batch reference absorbs them; rare DEL (< 5 %) 38 %. | Open: rare-event sensitivity as primary metric; phasing-based mosaic BAF (`docs/validation/V2_cn.md`). |
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| K-026 | 2026-09-29 | Methylation QC (v2) | Spec deviations: vendor EPIC manifests put a 5th field on some control lines (≥ 4 fields accepted); detection p follows sesame's pOOBAH (1 − max(F(M), F(U))) rather than the ambiguous "1 − ECDF(M + U)"; minfi-style `Sentrix_ID`/`Sentrix_Position` sheet keys accepted. Against sesame 1.28.1 on minfiDataEPIC: β r = 0.99998 (max \|Δβ\| 0.011), detection calls 99.1 % identical, noob signals within 0.5 % (median) / 5 % (max). The systematic remainder is unexplained; it is not the negative controls (sesame did not attach the supplied control table). | Open; `docs/validation/V2_methylation.md`. Next step: dump sesame's background vectors and noob parameters to find the difference. |
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@@ -92,4 +92,12 @@ so the per-call error is 1e-3 (GS ≥ 0.15) and errors are handled by the probe
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from the GRCh38 haplotype VCFs, `*1` = reference, prior reference 0.8 (no population frequencies); genotype only
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(no CPIC phenotype). The probe mask was re-derived with these variants (one more record: CYP2A6 19:40843845 C>A,
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concordance 0.47, which had produced false *5 calls).
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* Not yet: DPWG tables.
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* ClinPGx clinical-annotation variants (CC BY-SA 4.0; levels 1A–2B, and level 3 for the PGX-008 parity genes) add
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genotype-only variant-based genes — OPRM1, COMT, DRD2, ANKK1, MTHFR, F5, … (43 genes, 171 of 187 rsIDs resolved on
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GSA v4 PGx from the manifest's probes). The DB now holds 70 genes (16 star-allele, G6PD, 2 HLA tag, 51
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variant-based; spec parity list: 58). `pgx coverage`: 1225 alleles callable, 93 array-equivalent, 437 not
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covered, 5 masked.
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* `--guideline dpwg` (PGX-025): ClinPGx curates DPWG guidelines with the CPIC allele-function and phenotype mappings
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for genes CPIC covers, so those genes reuse the CPIC tables (flag `dpwg_via_cpic_mapping`); DPWG-only genes
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(CYP1A2, CYP3A4, F5) have no public machine-readable mapping and get phenotype `null` with the flag
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`dpwg_mapping_not_available` (K-029).
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@@ -56,3 +56,20 @@ files = {p.name: hashlib.sha256(p.read_bytes()).hexdigest() for p in sorted(d.gl
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"files": files}, indent=1))
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print("PharmVar version", ",".join(sorted(vers)))
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PY
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# ---- ClinPGx (formerly PharmGKB; CC BY-SA 4.0): clinical-annotation variants (variant-based genes, genotype only)
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CP="$OUT/clinpgx-$DATE"
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mkdir -p "$CP"
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curl -sSfL --retry 3 -o "$CP/clinicalVariants.zip" "https://api.clinpgx.org/v1/download/file/data/clinicalVariants.zip"
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python3 - "$CP" <<'PY'
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import hashlib, json, pathlib, sys, zipfile
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d = pathlib.Path(sys.argv[1])
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z = zipfile.ZipFile(d / "clinicalVariants.zip")
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created = next((n.split("_", 1)[1].rsplit(".", 1)[0] for n in z.namelist() if n.startswith("CREATED_")), "")
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(d / "source.json").write_text(json.dumps({"name": "ClinPGx clinical variants", "version": created,
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"retrieved": d.name.split("-")[1], "url": "https://www.clinpgx.org",
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"license": "CC BY-SA 4.0",
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"files": {"clinicalVariants.zip": hashlib.sha256(
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(d / "clinicalVariants.zip").read_bytes()).hexdigest()}}, indent=1))
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print("ClinPGx clinical variants", created)
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PY
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@@ -258,3 +258,32 @@ def pharmvar_core_alleles(gene: str, vcfs: dict[str, str]) -> dict[str, list[tup
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recs.append((f[0], int(f[1]), f[3].upper(), alt.upper(), rsid))
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out[f"*{m.group(1)}"] = recs
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return out
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CLINPGX_LEVELS = ("1A", "1B", "2A", "2B")
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# PGX-008 parity list of variant-based genes: level-3 annotations are kept for these too
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PARITY_VARIANT_GENES = {"DPYD", "RYR1", "OPRM1", "CFTR", "DRD2", "COMT", "OPRD1", "CACNA1C", "HTR2A", "OPRK1",
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"MT-RNR1", "TNF", "BDNF", "IL6", "HTR2C", "GRIN2B", "MTHFR", "ITGB3", "FKBP5", "ADH1B",
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"ANKK1", "HMGCR", "ATM", "KIF6", "F2", "CACNA1S", "LPA", "F13A1", "GRIK1", "GRIK4", "YEATS4",
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"ABCG2", "F5", "ALDH2", "ANK3", "VKORC1"} # fmt: skip
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def clinpgx_variant_genes(tsv: str, exclude: set[str], levels: tuple[str, ...] = CLINPGX_LEVELS) -> dict[str, set[str]]:
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"""ClinPGx ``clinicalVariants.tsv`` → gene → rsIDs with a clinical annotation at the given evidence levels, for
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single-gene rows of genes that no allele-definition source covers (level 3 as well for the PGX-008 parity genes)
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[DB: ClinPGx clinical annotations, CC BY-SA 4.0].
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Positions and alleles are resolved later from the manifest's probes (genotype-only variant-based genes)."""
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out: dict[str, set[str]] = {}
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lines = tsv.splitlines()
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head = lines[0].split("\t")
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iv, ig, il = head.index("variant"), head.index("gene"), head.index("level of evidence")
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for ln in lines[1:]:
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f = ln.split("\t")
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if len(f) <= max(iv, ig, il):
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continue
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gene, var, lev = f[ig].strip(), f[iv].strip(), f[il].strip()
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ok_level = lev in levels or (lev == "3" and gene in PARITY_VARIANT_GENES)
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if "," in gene or not gene or gene in exclude or not ok_level or not re.fullmatch(r"rs\d+", var):
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continue
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out.setdefault(gene, set()).add(var)
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return out
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@@ -254,6 +254,47 @@ def run_db_build(o: PgxDbOptions, rep: Reporter) -> int:
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hg = full_hgvs(ps.contig, f"g.{ps.pos}{ps.ref}>{alt}")
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tag_rows[(gene, allele)] = (gene, allele, "GRCh38", ps.contig, ps.pos, ps.ref, alt, hg, rsid, -1, alt)
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rows["probe_map"].append((name, ps.name, ps.contig, ps.pos, ps.ref, alt))
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# ClinPGx clinical-annotation variants of genes no definition source covers: genotype-only variant-based genes
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cp_src = None
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cdir2 = _latest(o.sources, "clinpgx")
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if cdir2 is not None:
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import zipfile
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from simurg.pgx.db import clinpgx_variant_genes
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cp_src = json.loads((cdir2 / "source.json").read_text())
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with zipfile.ZipFile(cdir2 / "clinicalVariants.zip") as z:
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tsv = z.read("clinicalVariants.tsv").decode()
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known = {g for g, *_ in rows["genes"]} | {g for g, *_ in TAGS}
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cp_genes = clinpgx_variant_genes(tsv, known)
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resolved: dict[tuple[str, str], tuple[Any, ...]] = {}
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want = {rs for v in cp_genes.values() for rs in v}
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for bpm_path in o.manifests:
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name = read_bpm(bpm_path).manifest_name
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for ps in _probe_sites(bpm_path, csvs.get(bpm_path), genome, cmap, {}, rep, want):
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alts = [a for a in ps.alleles if a != ps.ref]
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if len(alts) != 1 or ps.ref not in ps.alleles:
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continue
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for rs in re.findall(r"rs\d+", ps.name):
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if rs in want:
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hg = full_hgvs(ps.contig, f"g.{ps.pos}{ps.ref}>{alts[0]}")
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resolved.setdefault((rs, ps.contig), (ps.contig, ps.pos, ps.ref, alts[0], hg))
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rows["probe_map"].append((name, ps.name, ps.contig, ps.pos, ps.ref, alts[0]))
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by_rs = {rs: v for (rs, _), v in resolved.items()}
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lid2 = 950_000_000
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for gene in sorted(cp_genes):
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chrom = None
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rows["alleles"].append((gene, "Reference", "reference", None, None, 0, 1))
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for rs in sorted(cp_genes[gene], key=lambda r: int(r[2:])):
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v = by_rs.get(rs)
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rows["alleles"].append((gene, rs, "rsid_variant_allele", None, None, 0, int(v is not None)))
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if v is not None:
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lid2 += 1
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chrom = v[0]
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rows["allele_variants"].append((gene, rs, "GRCh38", v[0], v[1], v[2], v[3], v[4], rs, lid2, v[3]))
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rows["genes"].append((gene, "variant_based", chrom))
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rep.info(f"ClinPGx: {len(cp_genes)} variant-based gene(s), {len(by_rs)} of {len(want)} rsID(s) resolved "
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f"on the manifest(s)") # fmt: skip
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if tag_rows: # PGX-007: tag alleles become defined single-variant alleles
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rows["allele_variants"] += list(tag_rows.values())
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rows["alleles"] = [(g, a, k, f, act, sv, 1 if (g, a) in tag_rows else d) for g, a, k, f, act, sv, d in
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@@ -270,7 +311,10 @@ def run_db_build(o: PgxDbOptions, rep: Reporter) -> int:
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"license": csrc.get("license")}]
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+ ([{"name": "PharmVar", "version": pv_src["version"],
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"retrieved": pv_src["retrieved"], "license": pv_src.get("license")}]
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if pv_src else [])),
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if pv_src else [])
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+ ([{"name": "ClinPGx clinical variants", "version": cp_src["version"],
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"retrieved": cp_src["retrieved"], "license": cp_src.get("license")}]
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if cp_src else [])),
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"phenotype_sources": json.dumps([{"name": "CPIC", "version": csrc["version"]}]),
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"cpic_files_sha256": json.dumps(csrc.get("files", {}), sort_keys=True),
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"manifests": json.dumps(sorted(manifests)), "definition_notes": json.dumps(problems)} # fmt: skip
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@@ -301,8 +345,9 @@ def run_db_build(o: PgxDbOptions, rep: Reporter) -> int:
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rep.info(f"identical PGx DB already present: {final}")
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return ExitCode.OK
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tmp.replace(final)
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rep.info(f"PGx DB: {len(defs)} genes, {len(rows['alleles'])} alleles, {len(rows['allele_variants'])} variant "
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f"rows, {len(rows['probe_map'])} probe links → {final} (content sha256 {sha})") # fmt: skip
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n_g, n_a, n_v, n_p = (len(rows[k]) for k in ("genes", "alleles", "allele_variants", "probe_map"))
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rep.info(f"PGx DB: {n_g} genes, {n_a} alleles, {n_v} variant rows, {n_p} probe links → {final} "
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f"(content sha256 {sha})") # fmt: skip
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return ExitCode.OK
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@@ -17,6 +17,11 @@ from simurg.core.log import Reporter
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from simurg.pgx.phenotype import build_table, gene_phenotype
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JSON_SCHEMA = "simurg.pgx/1"
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# PGX-025 DPWG gene coverage. ClinPGx curates DPWG guidelines with the CPIC allele-function and phenotype mappings for
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# genes CPIC covers [DOC: ClinPGx, "Genotype-phenotype mapping for curation of DPWG guidelines"], so those genes use the
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# CPIC tables (flag dpwg_via_cpic_mapping); DPWG-only genes have no public machine-readable mapping here.
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DPWG_GENES = ("CYP1A2", "CYP2B6", "CYP2C19", "CYP2C9", "CYP2D6", "CYP3A4", "CYP3A5", "DPYD", "NUDT15", "SLCO1B1",
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"TPMT", "UGT1A1", "VKORC1", "F5") # fmt: skip
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TSV_SCHEMA = "simurg.pgx_tsv/1"
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@@ -65,9 +70,8 @@ def run_phenotype(o: PhenoOptions, rep: Reporter) -> int:
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"""``simurg pgx phenotype`` (CLI-034)."""
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from simurg.core.atomic import atomic_write_text
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if o.guideline != "cpic":
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raise SimurgError("E_PGX_GUIDELINE", f"guideline {o.guideline!r} is not in this PGx DB (CPIC only)",
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hint="DPWG tables are not built yet (K-029)") # fmt: skip
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if o.guideline not in ("cpic", "dpwg"):
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raise SimurgError("E_PGX_GUIDELINE", f"unknown guideline {o.guideline!r}", hint="cpic or dpwg")
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src = o.calls / "pgx_calls.json"
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if not src.exists():
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raise SimurgError("E_NO_INPUT", f"{src} not found", hint="run pgx star-allele call first")
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@@ -77,9 +81,11 @@ def run_phenotype(o: PhenoOptions, rep: Reporter) -> int:
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meta = db_meta(o.db)
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con = sqlite3.connect(o.db)
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tables = {}
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for (gene,) in con.execute("SELECT DISTINCT gene FROM phenotypes WHERE guideline = ?", (o.guideline,)):
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for (gene,) in con.execute("SELECT DISTINCT gene FROM phenotypes WHERE guideline = 'cpic'"):
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if o.guideline == "dpwg" and gene not in DPWG_GENES:
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continue
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rows = con.execute("SELECT lookup_key, activity_score, phenotype FROM phenotypes WHERE gene = ? AND "
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"guideline = ?", (gene, o.guideline)).fetchall() # fmt: skip
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"guideline = 'cpic'", (gene,)).fetchall() # fmt: skip
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alle = con.execute("SELECT allele, function, activity FROM alleles WHERE gene = ?", (gene,)).fetchall()
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tables[gene] = build_table(gene, rows, alle)
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tested = {g: [a for (a,) in con.execute("SELECT allele FROM alleles WHERE gene = ? AND defined = 1", (g,))]
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@@ -104,6 +110,8 @@ def run_phenotype(o: PhenoOptions, rep: Reporter) -> int:
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elif g.get("call_type") == "copy_number":
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res, per = None, []
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flags = list(g.get("flags", [])) + (res.flags if res else [])
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if o.guideline == "dpwg" and g["gene"] in DPWG_GENES:
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flags.append("dpwg_via_cpic_mapping" if t is not None else "dpwg_mapping_not_available")
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top = g["candidates"][0] if g["candidates"] else {}
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top_alleles = top.get("alleles", [])
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entry = {"gene": g["gene"], "call_type": g.get("call_type", "star_allele"), "genotype": g["genotype"],
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@@ -156,3 +156,46 @@ def test_pharmvar_core_alleles() -> None: # PGX-001 PharmVar source
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core = pharmvar_core_alleles("CYP2A6", {"CYP2A6-6.2/GRCh38/CYP2A6_9.vcf": vcf,
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"CYP2A6-6.2/GRCh38/CYP2A6_9.001.vcf": vcf}) # fmt: skip
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assert core == {"*9": [("chr19", 100, "A", "C", "rs1")]} # sub-alleles (*9.001) are not core definitions
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def test_clinpgx_variant_genes() -> None: # PGX-008 variant-based genes from ClinPGx
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from simurg.pgx.db import clinpgx_variant_genes
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tsv = ("variant\tgene\ttype\tlevel of evidence\tchemicals\tphenotypes\n"
|
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"rs1\tOPRM1\tEfficacy\t3\tx\t\nrs2\tFOO\tEfficacy\t3\tx\t\nrs3\tFOO\tEfficacy\t2A\tx\t\n"
|
||||
"CYP2C9*3\tCYP2C9\tPK\t1A\tx\t\nrs4\tCYP2C9\tPK\t1A\tx\t\nrs5\tA,B\tPK\t1A\tx\t\n") # fmt: skip
|
||||
assert clinpgx_variant_genes(tsv, {"CYP2C9"}) == {"OPRM1": {"rs1"}, "FOO": {"rs3"}}
|
||||
|
||||
|
||||
def test_dpwg_mode(tmp_path: Path) -> None: # PGX-025
|
||||
from simurg.core.log import Reporter
|
||||
from simurg.pipeline.pgx_pheno import PhenoOptions, run_phenotype
|
||||
|
||||
src = tmp_path / "sources" / "cpic-20260101"
|
||||
src.mkdir(parents=True)
|
||||
t = _tables()
|
||||
t["gene"][0]["symbol"] = "CYP2D6"
|
||||
for tbl in ("sequence_location", "allele_definition", "allele", "gene_result"):
|
||||
for r in t[tbl]:
|
||||
r["genesymbol"] = "CYP2D6"
|
||||
for k, v in t.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")
|
||||
r = CliRunner().invoke(app, ["pgx", "db", "build", "--sources", str(tmp_path / "sources"), "--fasta", str(fa),
|
||||
"--out", str(tmp_path / "db"), "--quiet"]) # fmt: skip
|
||||
assert r.exit_code == 0, r.output
|
||||
db = next((tmp_path / "db").glob("pgx_db-1-*.sqlite"))
|
||||
calls = tmp_path / "calls"
|
||||
calls.mkdir()
|
||||
(calls / "pgx_calls.json").write_text(json.dumps({"samples": [{"sample_id": "s1", "genes": [
|
||||
{"gene": "CYP2D6", "genotype": "*2/*2", "feasible_solutions": ["*2/*2"], "candidates": [
|
||||
{"genotype": "*2/*2", "score": 1.0, "raw_score": 1.0}]},
|
||||
{"gene": "CYP3A4", "genotype": "*1/*22", "feasible_solutions": ["*1/*22"], "candidates": []}]}]})) # fmt: skip
|
||||
rep = Reporter(command="t", quiet=True)
|
||||
assert run_phenotype(PhenoOptions(calls, db, guideline="dpwg"), rep) == 0
|
||||
doc = json.loads((calls / "s1.pgx.json").read_text())
|
||||
by = {g["gene"]: g for g in doc["genes"]}
|
||||
assert by["CYP2D6"]["phenotype"] == "Poor Metabolizer" and "dpwg_via_cpic_mapping" in by["CYP2D6"]["flags"]
|
||||
assert by["CYP3A4"]["phenotype"] is None and "dpwg_mapping_not_available" in by["CYP3A4"]["flags"]
|
||||
Reference in new issue
Block a user