Blood manifest: 183 samples Loaded 86,446,638 rows from 183 blood samples in 108.2s GC reference: 472,386 probes Sex chrom homology mask: 1494 probes Pass 1: 4-feat blood GAM (16 workers)... 20/183 blood samples, 27s, R²=0.4570 40/183 blood samples, 40s, R²=0.4652 60/183 blood samples, 54s, R²=0.4771 80/183 blood samples, 68s, R²=0.4639 100/183 blood samples, 83s, R²=0.4516 120/183 blood samples, 95s, R²=0.4208 140/183 blood samples, 112s, R²=0.4831 160/183 blood samples, 127s, R²=0.4769 180/183 blood samples, 138s, R²=0.5122 183/183 blood samples, 140s, R²=0.4682 Sex: 94 female, 89 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: 472,051/472,386 valid probes Preliminary 5-feat GAM on blood (16 workers)... 20/183 blood prelim 5-feat, 39s, R²=0.9388 40/183 blood prelim 5-feat, 57s, R²=0.9365 60/183 blood prelim 5-feat, 77s, R²=0.9473 80/183 blood prelim 5-feat, 96s, R²=0.9450 100/183 blood prelim 5-feat, 119s, R²=0.9342 120/183 blood prelim 5-feat, 143s, R²=0.9372 140/183 blood prelim 5-feat, 162s, R²=0.9361 160/183 blood prelim 5-feat, 183s, R²=0.9536 180/183 blood prelim 5-feat, 201s, R²=0.9291 183/183 blood prelim 5-feat, 206s, R²=0.9458 /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: 25,527 masked (5.4%) — 12,266 low cov, 20,394 high var, 4,604 extreme Wrote batch_reference.parquet (472,386 probes) to ./batch_reference.parquet Wrote sex_calls.csv (183 samples) to ./sex_calls.csv Wrote feature_stats.csv (183 samples) to ./feature_stats.csv Build reference complete in 1735.2s total