- genotype/clusters.py: EGT aligned to manifest order (float32 mean R)
- genotype/gencall.py: flair, six-case likelihood, priors/posteriors,
fuzzy sub-scores and score map, vectorised with the reference's
float/double evaluation order and libm transcendentals
- genotype/baf_lrr.py, sex.py (rules v1/v2), sample.py (IDAT -> Gtc)
- pipeline/inputs.py shared by ingest and genotype
- pipeline/genotype.py + CLI: GTC per sample, sample_summary.tsv/json
(OUT-060..063), run manifest
- GTCs from IDATs are byte-identical to the oracle for 36 GSA samples x
2 normalization versions (NaN sign canonicalised to the x86 pattern)
Normalization 1.1.2 reproduces all 109,191 bins of the 1000 Genomes
Omni2.5 GTCs (AutoCall 1.6.2.2) with 0 ULP difference, reserved fields
included; 1.2.0 and 1.1.2 are bit-identical to the no-FMA gtc2vcf oracle
on 36 GSA samples. AWS run: 33 min, ~$0.15, no resources left.
Raw X/Y and controls assembled from IDATs equal the vendor GTC arrays for
2138/2141 samples x 2.45M loci; 3 single-locus differences are recorded
as K-009 (probable per-channel missing rule in AutoCall 1.6.2.2). Channel
order X=Red confirmed (U1). `simurg ingest` processed all 2141 samples in
19 min (I/O-bound). AWS run cost ~$0.34 and left no resources.
All 2141 vendor-written GTC v3 files match BeadArrayFiles field by field
and re-encode byte-identically; all IDAT pairs parse; the 2.45M-locus BPM,
dbv-7 EGT and CSV manifest agree with BeadArrayFiles and each other.
Run on a self-destructing AWS spot instance (42 min, ~$0.20).
Research notes R1-R4, documentation-study files A-E (source of the
functional spec's `src:` tags) and PGx coverage CSVs, rewritten to use
neutral naming and current project decisions (plan §2).
kemal