kemalandClaude Opus 5.5
ed4895516d
Graviton3 c7g.8xlarge, 360 GSE165845 arrays: 360/360 GTCs identical between the Rust kernels and the pure-Python paths; 1 worker 78-80 samples/min (pure Python 29.6). Scaling 1->8 workers efficiency 0.87-0.90; above that the 125 MB/s gp3 disk caps the run (~620 samples/min) and, on a RAM disk, a fixed per-worker start-up cost limits a 360-sample batch to efficiency 0.48 at 32 workers (K-025). Worker state is pickled once. docs/validation/P9.md, result JSONs, guide/README/CHANGELOG updates. Co-Authored-By: Claude Opus 5.5 <[email protected]> Claude-Session: https://claude.ai/code/session_01814GKVzZVL3FuF3DeiZXhv
46 lines
2.8 KiB
Markdown
46 lines
2.8 KiB
Markdown
# SimurgArray
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Personal research toolkit for Illumina Infinium genotyping BeadChip data
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(IDAT → normalization → genotype calling → BAF/LRR → QC → VCF/PLINK; later CN/LOH, PGx, cluster training).
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- **SIMURGARRAY_MASTER_PLAN.md** — architecture, algorithms, roadmap
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- **SIMURGARRAY_FUNCTIONAL_SPEC.md** — 416 itemised requirements (CLI, inputs, outputs, QC, CN, PGx, methylation, edge cases)
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- `docs/validation/` — per-phase validation reports · `docs/known_unknowns.md` — findings log · `docs/research/` — background
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## Status
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**v1.0.0** (2026-09-28) — see `CHANGELOG.md`. IDAT → normalization → GenCall-equivalent genotype calling → GTC v5 →
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sample/control QC with an HTML report → plus-strand VCF/BCF → PLINK 1/2, bedGraph, final report; plus a
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differential-testing harness. Validation (`docs/validation/`):
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| Check | Result |
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|---|---|
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| 2141 vendor GTCs, 1000 Genomes Omni2.5 (`--preset autocall-1.6.2`) | normalization bit-identical; GTCs byte-identical in 2138/2141 |
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| GSA demo vs gtc2vcf, GTCtoVCF, plink2 | zero unexplained differences |
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| 1000 Genomes pedigrees (Omni2.5) | 717/717 parent–offspring pairs; Mendel error median 0.031 % |
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| 360 GSA arrays (GSE165845) vs NYGC 30x WGS / GIAB HG001 | concordance 0.9934 / 0.9985; replicates 0.9966 |
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Commands: `simurg inspect`, `ingest`, `normalize`, `genotype`, `qc controls|samples|contamination|relatedness|loci|report|suggest-thresholds`,
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`gtc-to-vcf`, `export plink|bedgraph|finalreport|locus-summary`, `compare`. **User guide: `docs/user_guide.md`**;
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worked example: `examples/gsa_demo.sh`. P9 (performance) is done: optional Rust kernels, byte-identical outputs,
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~80 GSA samples/min per server core (`docs/validation/P9.md`). Next (plan §18): P10 packaging, then v2 modules
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(cluster training, CN/LOH, PGx).
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## Quick start
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```bash
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uv venv && uv pip install -e ".[dev]"
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uv run pytest tests/unit # no downloads needed
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bash scripts/bootstrap_refs.sh # reference open-source repos → refs/ (oracles)
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bash scripts/fetch_data.sh p0 # ~1.4 GB of public test data → data/
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bash scripts/make_oracle_gtcs.sh # builds gtc2vcf, writes oracle GTCs
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bash scripts/make_oracle_qc.sh # locus-summary oracle (BeadArrayFiles, separate venv)
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bash scripts/fetch_data.sh p6 # GRCh38 FASTA (~0.9 GB download, 3.1 GB unpacked)
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bash scripts/make_oracle_vcf.sh # gtc2vcf oracle VCF for the P6 tests
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uv run pytest tests/oracle # real-data acceptance tests (add -m "not slow" to skip the long ones)
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uv run simurg inspect data/p0/gsa_v4_pgx/idats_Demo_36/idats_Demo_36/207895980019/207895980019_R03C01_Grn.idat
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bash examples/gsa_demo.sh results/gsa_demo 6 # end-to-end run on 6 demo samples
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```
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Vendor data files are downloaded for personal research use only and are never committed. See `THIRD_PARTY_NOTICES.md`.
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