kemalandClaude Opus 5.5
58e70bc894
- simurg/pgx/cn.py: per-region CN mixture, mu_c = delta + gamma*log2((c+1)/3), free lower CN-0 component, Hardy-Weinberg-constrained weights over haplotype copy numbers, EM from a grid of label starts. - pipeline/pgx_cn.py: model file (.simurg-pgxcn), batch rules (PCN-004), per-sample CN VCF + tbi, batch and sample summaries. - The GSA v4 PGx demo arrays are 30 CEPH/1000G individuals (scripts/pgx/demo36_identity.tsv); against NYGC 30x SV RD_CN 224/240 region calls agree (GSTM1, UGT2B17 30/30), in-sample (docs/validation/V2_pgx_cn.md). Co-Authored-By: Claude Opus 5.5 <[email protected]> Claude-Session: https://claude.ai/code/session_01814GKVzZVL3FuF3DeiZXhv
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2.8 KiB
V2 — Targeted PGx copy number (PCN-001 … PCN-017)
Status: implemented, interim validation (2026-09-29). simurg pgx copy-number train|call (CLI-031/032), model
file .simurg-pgxcn (IN-050), region BED v1 built from UCSC ncbiRefSeq (scripts/pgx/build_cn_regions.py,
packaged as simurg/pgx/data/pgx_cn_regions.GRCh38.v1.bed), per-sample *.pgx_cn.vcf.gz + .tbi,
pgx_cn_batch_summary.tsv, pgx_cn_sample_summary.tsv. Unit tests: tests/unit/test_pgx_cn.py.
Data
- Arrays: the GSA v4 PGx demo (
idats_Demo_36, 36 arrays), genotyped by SimurgArray. Its CNV probes cover every region (51–357 probes; GSTT1: 160 probes onchr22_KI270879v1_altin the GRCh38 manifest). - Identities: the demo arrays are 30 CEPH / 1000 Genomes individuals (6 replicate arrays). Identified by
genotype concordance with the 3202-sample 1000G 30x panel on 4647 chr22 SNPs: best match 0.992–0.996, next best
≤ 0.91 (relatives) —
scripts/pgx/demo36_identity.tsv. - Truth: NYGC 30x SV callset (1KGP_3202 GATK-SV/svtools freeze V3), RD_CN per individual
(
scripts/pgx/validate_cn_truth.py). - The GSE165845 GSA-MD v1 arrays (360 arrays, CN/LOH validation) have 0–9 probes per PGx region: not usable here.
Result (30 individuals, model trained on the same 36 arrays with --min-samples 30)
| Region | Concordance with NYGC RD_CN | Mismatches (truth → call) |
|---|---|---|
| GSTM1 (whole gene) | 30/30 | – |
| UGT2B17 (whole gene) | 30/30 | – |
| SULT1A1 | 29/30 | 2→1 |
| CYP2A6.exon.1 | 29/30 | 3→2 |
| CYP2A6.intron.7 | 28/30 | 3→2, 1→2 |
| CYP2D6.p5 | 28/30 | 4→3, 2→1 |
| CYP2D6.intron.2 | 25/30 | 3→2 ×3, 4→3, 2→1 |
| CYP2D6.exon.9 | 25/30 | 3→2 ×3, 4→2, 2→1 |
| all | 224/240 (93.3 %) |
GSTT1 (no SV truth on the alt contig): CN 0/1/2 = 5/16/9, in Hardy–Weinberg proportions (null allele 0.43; CEU
literature ≈ 0.4–0.5). Details: V2_pgx_cn_demo36.json.
- CYP2D6 truth is one gene-level record; the exon-9 / intron-2 "misses" at truth CN 3 are expected for tandem
structures such as
*68+*4or*36+*10, where not every sub-region is duplicated. Star-allele truth (GeT-RM) is the right yardstick and follows with the star-allele caller. - PCN-017 target (≥ 95 % per region) is met for GSTM1, UGT2B17, SULT1A1, CYP2A6.exon.1; not (yet) shown for the CYP2D6 sub-regions.
Caveats (K-028)
- Trained and evaluated on the same 30 individuals (the spec requires ≥ 96 training samples; the priors were chosen while looking at this truth). This is an optimistic, in-sample figure until an independent cohort is available.
- Deviations from PCN-009: reference from the training cohort (not the calling batch); no GC-correction step; CN
model = compressed-intensity template + HWE-constrained weights (
simurg/pgx/cn.py).