Blood manifest: 182 samples Loaded 85,974,252 rows from 182 blood samples in 109.5s GC reference: 472,386 probes Sex chrom homology mask: 1494 probes Pass 1: 4-feat blood GAM (16 workers)... 20/182 blood samples, 26s, R²=0.3801 40/182 blood samples, 39s, R²=0.4652 60/182 blood samples, 55s, R²=0.4642 80/182 blood samples, 69s, R²=0.4792 100/182 blood samples, 82s, R²=0.4092 120/182 blood samples, 95s, R²=0.4168 140/182 blood samples, 113s, R²=0.4561 160/182 blood samples, 128s, R²=0.4870 180/182 blood samples, 140s, R²=0.4156 182/182 blood samples, 140s, R²=0.4589 Sex: 103 female, 79 male, 0 unknown /usr/local/bin/build_norm_reference.py:247: RuntimeWarning: All-NaN slice encountered probe_coverage_median = np.nanmedian(blood_matrix, axis=1) /usr/local/lib/python3.12/site-packages/numpy/lib/_nanfunctions_impl.py:1593: RuntimeWarning: All-NaN slice encountered return fnb._ureduce(a, Probe coverage: 471,938/472,386 valid probes Preliminary 5-feat GAM on blood (16 workers)... 20/182 blood prelim 5-feat, 40s, R²=0.9432 40/182 blood prelim 5-feat, 59s, R²=0.9408 60/182 blood prelim 5-feat, 80s, R²=0.9309 80/182 blood prelim 5-feat, 101s, R²=0.9548 100/182 blood prelim 5-feat, 124s, R²=0.9505 120/182 blood prelim 5-feat, 149s, R²=0.9383 140/182 blood prelim 5-feat, 169s, R²=0.9500 160/182 blood prelim 5-feat, 189s, R²=0.9566 180/182 blood prelim 5-feat, 206s, R²=0.9494 182/182 blood prelim 5-feat, 207s, R²=0.9422 /usr/local/bin/build_norm_reference.py:335: RuntimeWarning: All-NaN slice encountered prelim_median = np.nanmedian(prelim_matrix, axis=1) /usr/local/lib/python3.12/site-packages/numpy/lib/_nanfunctions_impl.py:1593: RuntimeWarning: All-NaN slice encountered return fnb._ureduce(a, Probe mask: 21,946 masked (4.6%) — 10,943 low cov, 16,810 high var, 3,441 extreme Wrote batch_reference.parquet (472,386 probes) to ./batch_reference.parquet Wrote sex_calls.csv (182 samples) to ./sex_calls.csv Wrote feature_stats.csv (182 samples) to ./feature_stats.csv Build reference complete in 1734.2s total