# Changelog

## Unreleased (v2)

**Methylation control QC** (`simurg methyl qc`, `simurg methyl convert-manifest`; MET-001 … MET-018): methylation
CSV manifests, the 21 control metrics, pOOBAH detection p-values, noob, linear/nonlinear dye bias, β and M-values,
summary tsv/xlsx/html with a β PCA, per-sample tables; methylation folders load in `simurg qc report`;
`qc controls --array-type methylation`. Checked against sesame (`docs/validation/V2_methylation.md`, K-026).

## 1.1.0 — 2026-09-28 (P9, P10)

**Packaging (P10).** `scripts/build_dist.sh` (sdist, pure wheel, manylinux_2_28 kernel wheels for x86_64 and
aarch64), `Dockerfile`, conda recipes (`packaging/conda/`). Verified on fresh x86_64 and aarch64 VMs: pip, Docker
and conda installs give identical outputs (`docs/validation/P10.md`). A closed stdout pipe now exits 141 silently
instead of reporting an internal error.

**Performance (P9).**

Optional compiled kernels `rust/simurg-core` (PyO3): fused GenCall calling and BAF/LRR, libm maps with CPython
semantics, normalization nearest-neighbour searches, BPM parser. Byte-identical outputs to the pure-Python paths
(`SIMURG_PURE_PYTHON=1`); 78–80 GSA samples/min per Graviton3 core (pure Python 30), manifest loading 4× faster.
Address coverage memoised per IDAT layout; worker state pickled once. `bench/profile_genotype.py`,
`bench/scaling.py`. Details and scaling limits: `docs/validation/P9.md`.

## 1.0.0 — 2026-09-28

First release: the v1.0 goals of the master plan (§1.1), built and validated phase by phase (P0–P8).

**Formats (P1–P2).** Readers for IDAT (plain or gzipped; encrypted v1 refused), BPM, CSV manifest, EGT, GTC v3–v5
and sample sheets; `simurg inspect`; raw X/Y assembly into a canonical Parquet model (`simurg ingest`, resumable).

**Signal and calling (P3–P4).** Per-bin affine normalization 1.2.0 and 1.1.2; GenCall-equivalent calling from an
EGT with GenCall score; θ/R, BAF, LRR, LogR deviation, GC10/GC50, intensity percentiles, sex (rules 1 and 2);
GTC v5/v3 writer (`simurg genotype`). Presets `current` and `autocall-1.6.2`.

**QC (P5).** Control-probe metrics, threshold profiles and YAML, two-axis sample status and flags,
BAF-regression contamination, KING-robust relatedness and Mendel errors, locus summary, threshold suggestion, a
self-contained HTML QC report with xlsx/csv table (`simurg qc …`).

**Outputs (P6).** Plus-strand harmonisation with an audit trail; per-sample VCF.gz + tabix or cohort BCF + CSI
(`GT:GS:BAF:LRR`, optional INFO and intensity fields, merged multi-probe sites, indels from SourceSeq, SNV+indel
merging, auxiliary MNV loci); PLINK 1 `.bed` and PLINK 2 `.pgen`; BAF/LRR bedGraph; final report and genotype matrix.

**Testing (P7).** `simurg compare` (EXACT/NEAR/DISCREPANCY/UNKNOWN per field and locus class, HTML dashboard) and a
nightly differential run against gtc2vcf, GTCtoVCF and vendor GTCs.

**Validation (P8).** 360 GSA arrays of 120 1000 Genomes individuals vs NYGC 30x WGS (concordance 0.9934) and
GIAB HG001 (0.9985, non-ref F1 0.997); replicate concordance 0.9966. Vendor-equivalence: 2138/2141 Omni2.5 GTCs
byte-identical, zero unexplained VCF/PLINK differences vs gtc2vcf, GTCtoVCF and plink2.

Documentation: `docs/user_guide.md`, `examples/`, `docs/validation/P1.md … P8.md`, `docs/known_unknowns.md`,
`docs/messages.md`.

Known limitations: needs an existing cluster file (training is v2); no CN/LOH/PGx yet; largest tested cohort
2141 samples; pure NumPy speed.