Archive 4 checkpoints (1-4)

paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/scores/giroux2022/locoL_fullsat_s20000_K1000/summary.json

@@ -0,0 +1,531 @@
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+ "seconds": 9.3
+}

paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/scores/giroux2022/locoL_fullsat_s40000_K1000/README.md

@@ -0,0 +1,73 @@
+# score_ft.py output: giroux2022, 24 scored donors
+
+Arms: locoL_fullsat_s40000_K1000.  Every arm is scored on the same donors against the same observed reference.
+
+## Inputs and fixed contracts
+- Observed reference: `/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/giroux2022/reference.npz` (sha dd0152f7bde4), built from datadir:/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/giroux2022;
+  observed cells sum exactly to the features pseudobulk of every donor. Observed labels: /home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/giroux2022/observed_labels/labels/labels.parquet.
+- Generated cells: `generated_counts` read out once with Poisson(seed 20260916) over the **whole NPZ in row order**
+  (`poisson_readout.poisson_integerise`), then the scored donors' rows. These integer counts are used for labels, embedding,
+  depth and the contrast. Pseudobulk uses the summed `generated_counts` (rates), as `score_generated.py`.
+- Labels: frozen f01common scANVI (`predict_scanvi.py`, CPU, zero query epochs), six-type gate ['T cell', 'B cell', 'Monocyte', 'NK cell', 'DC', 'Other']; query genes =
+  the 1,006-gene annotation list minus genes the dataset's sc assay did not measure in every sample (1006 genes).
+- Scoring genes: 6k panel genes measured by both assays in every sample of the dataset (5563 genes).
+
+## Definitions
+1. **Composition**: fraction of each donor's cells per six-type label (all generated cells; all observed QC cells).
+   `comp_l1` = sum over the six labels of |generated - observed| (immicro_common.l1). `comp_l1_obs_loo_null` = L1 of the
+   donor's observed composition to the mean of the *other scored donors'* observed compositions. `composition_top1` =
+   fraction of donors whose generated composition is closest (L1) to their own observed composition.
+2. **Pseudobulk**: `pb_r` = Pearson r of CPM-log1p(summed generated_counts) vs CPM-log1p(observed pseudobulk) on the scoring
+   genes (evaluate_realbulk.cpm_log1p / paired_r). `pb_top1` = the donor's generated pseudobulk is closest (Pearson) to its own
+   observed pseudobulk among the 24 scored donors (immicro_common.retrieval = evaluate_realbulk.top1 arithmetic).
+3. **Precision / coverage / density** (stage_b_embed.py functions): per-cell CP10K over the scoring genes + log1p; PCA-50
+   (randomized, random_state 20260925) and k = 10 real-real k-NN balls fitted on **R1 of the scored donors only**.
+   Reference rule (independent of fold and arm): per donor, cells in canonical order (library_id+barcode), one
+   permutation from `default_rng([20260925, uint64(sha256(donor)[:8])])`; R1 = first n, R2 = next n,
+   n = min(150, n_cells // 2) (3600 R1 cells here). Generated query: per donor n cells (the donor's R1 size),
+   without replacement, `default_rng([20260926, same key])`. Precision = fraction of generated cells inside any R1 ball
+   (Kynkaanniemi 2019); coverage = fraction of R1 cells whose ball holds a generated cell; density = Naeem 2020.
+   Per-donor precision = that donor's generated cells; per-donor coverage = that donor's R1 cells (the pooled values are
+   their n-weighted means; plain means when every donor has 150 reference cells). R2 (held-out real cells of the same donors) is the
+   perfect-generator control: precision 0.9981, coverage 1.0000.
+   **Depth matched**: stage_b_embed depth matching run pairwise (R1 vs this arm): per donor and within-donor rank of detected
+   genes, both cells are thinned by UMI sampling without replacement to the smaller detected-gene count; PCA kept from
+   un-thinned R1, radii recomputed on thinned R1; fresh rng(20260929) per arm. R2 control: precision
+   0.9981, coverage 1.0000.
+4. **Monocyte %** = 100 x Monocyte fraction (all cells) per donor; **median UMI per cell** = median over cells of the
+   Poisson-read (generated) / observed counts summed over the scoring genes (per donor, and pooled).
+5. **Group contrast** (T, B, Monocyte, NK): case groups ['severe'] (n = 11) vs control groups ['mild'] (n = 13); rule: explicit --case-groups / --control-groups; groups from features groups.
+   Genes per type = scoring genes detected (count > 0) in >= 1 % of the scored donors' observed
+   cells of that type. Primary statistic `mean_cp10k`: per-cell CP10K over the scoring genes; per donor the mean over its
+   cells of the type (donors with >= 1 such cell); group mean = mean over the group's donors (donor-balanced);
+   logFC = log2(case mean + 1) - log2(control mean + 1). Secondary `pseudobulk_log1p_cpm`: the SLE benchmark evaluator's
+   statistic (donor x type summed counts, log1p CPM over the scoring genes, mean case - mean control;
+   evaluate_generated_vs_truth.group_log_fold_change). Both are computed on the generated cells (their frozen labels) and on
+   the observed cells; `r_generated` = Pearson r of the two logFC vectors. Broadcast baseline `r_broadcast`: the same
+   observed vector against the logFC of the input bulk (condition NPZ `bulk_counts` of the arm, scoring genes, per-donor
+   CP10K resp. log1p CPM, group means). `partial_r_generated_given_broadcast`: r of the OLS residuals of observed and
+   generated logFC on the bulk logFC (residual_specificity.py).
+6. **Top-50 DEG overlap** (contrast.csv rows `statistic = welch_top50_deg`; summary `deg_top50`): the SLE benchmark's score (`total_top50_overlap` of
+   `bulk2sc-paper/scripts/evaluate_generated_vs_truth.py`, Welch backend: the "top-50 DEG 81 / 84" of the final model), run
+   with the evaluator's own functions on the same donor x type pseudobulks as the contrast. Per cell type, observed and
+   generated separately: donor x type summed counts on all 5563 scoring genes (donors of the two groups with
+   >= 1 cell of the type) -> `welch_bh_deg` (log1p CPM, two-sided Welch t-test case vs control, Benjamini-Hochberg over the
+   genes with a defined p-value; needs >= 2 donors per group) -> `top_deg_genes` (FDR < 0.05, descending |logFC|,
+   first 50; shorter when fewer genes pass). `top50_overlap` = |observed list & generated list|; `top50_jaccard`
+   the evaluator's Jaccard. Summary `sum` = total over the scored types (the quantity reported as 81), `max` = the sum of
+   the observed list lengths (the "of 262"), `sum_4type` = T + B + Monocyte + NK. A type is scored when its observed test
+   is defined; an arm whose generated test is undefined for a scored type gets overlap 0. Types: T cell, B cell, Monocyte, NK cell, DC
+   (aggregates: /home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/giroux2022/deg_reference.npz).
+   **Broadcast analogue** (`top50_overlap_broadcast`, as `sle_broadcast.py` `broadcast_input_bulk`; not part of the
+   published benchmark): the same test on the arm's condition bulk_counts (scoring genes, the 11 + 13
+   donors), one whole-PBMC top-50 list, compared with every type's observed list.
+
+## Files
+- `per_donor.csv`: one row per arm x donor (all per-donor quantities above).
+- `summary.json`: per arm the donor means / pooled values, provenance (NPZ sha, receipt check, generation metadata,
+  Poisson nnz of the whole NPZ, annotation contract), and the reference block (PCA, R2 control).
+- `contrast.csv`: per arm x cell type x statistic (`mean_cp10k`, `pseudobulk_log1p_cpm`: logFC r; `welch_top50_deg`:
+  top-50 DEG overlap, T / B / Monocyte / NK / DC; columns of the other kind are empty).
+- `arms/<arm>/labels/` (predict_scanvi.py labels + manifest), `arms/<arm>/generated_cells.parquet` (NPZ row, donor, label,
+  UMI on the scoring genes, P/C subsample flag), `arms/<arm>/deg_top50_lists.csv` (observed, generated and broadcast
+  top-50 gene lists, Ensembl ids, rank order).

paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/scores/giroux2022/locoL_fullsat_s40000_K1000/contrast.csv

@@ -0,0 +1,14 @@
+arm,celltype,statistic,n_genes,r_generated,r_broadcast,partial_r_generated_given_broadcast,r_generated_vs_broadcast,n_case_donors_obs,n_control_donors_obs,n_case_donors_gen,n_control_donors_gen,n_cells_obs,n_cells_gen,deg_scored,top50_overlap,top50_jaccard,obs_top_list_size,gen_top_list_size,n_sig_obs,n_sig_gen,top50_overlap_broadcast,top50_jaccard_broadcast,broadcast_top_list_size,n_sig_broadcast
+locoL_fullsat_s40000_K1000,T cell,mean_cp10k,2908,0.46932725269394765,0.6665223768938867,0.25655100422511656,0.4475390266721928,11,13,11,13,145034,29104,,,,,,,,,,,
+locoL_fullsat_s40000_K1000,T cell,pseudobulk_log1p_cpm,2908,0.5383488531089596,0.829771536027708,0.17691143907300924,0.5493654019732782,11,13,11,13,145034,29104,,,,,,,,,,,
+locoL_fullsat_s40000_K1000,B cell,mean_cp10k,3053,0.22433537515876956,0.5741068019580355,0.13625611310945251,0.20037043308937058,11,13,11,13,17383,2540,,,,,,,,,,,
+locoL_fullsat_s40000_K1000,B cell,pseudobulk_log1p_cpm,3053,0.20230484369929935,0.7295906969005199,0.06797021726571943,0.21506417135302636,11,13,11,13,17383,2540,,,,,,,,,,,
+locoL_fullsat_s40000_K1000,Monocyte,mean_cp10k,3056,0.08406538113168435,0.6998157471451955,0.03460144345250748,0.08493388716145735,11,13,10,13,47311,1463,,,,,,,,,,,
+locoL_fullsat_s40000_K1000,Monocyte,pseudobulk_log1p_cpm,3056,-0.00098386297815451,0.8460762046394,-0.0702796730273767,0.043075062459011985,11,13,10,13,47311,1463,,,,,,,,,,,
+locoL_fullsat_s40000_K1000,NK cell,mean_cp10k,2955,0.16680424189324086,0.6119759414285395,0.10002438697197275,0.144661614852134,11,13,11,13,29061,2130,,,,,,,,,,,
+locoL_fullsat_s40000_K1000,NK cell,pseudobulk_log1p_cpm,2955,0.06604152065079681,0.7735167267842559,-0.003960611456533807,0.08861060696223354,11,13,11,13,29061,2130,,,,,,,,,,,
+locoL_fullsat_s40000_K1000,T cell,welch_top50_deg,5563,,,,,11,13,11,13,145034,29104,True,6,0.06382978723404255,50,50,306,83,10,0.1724137931034483,18,18
+locoL_fullsat_s40000_K1000,B cell,welch_top50_deg,5563,,,,,11,13,11,13,17383,2540,True,4,0.4,9,5,9,5,7,0.35,18,18
+locoL_fullsat_s40000_K1000,Monocyte,welch_top50_deg,5563,,,,,11,13,10,13,47311,1463,True,1,0.034482758620689655,7,23,7,23,7,0.3888888888888889,18,18
+locoL_fullsat_s40000_K1000,NK cell,welch_top50_deg,5563,,,,,11,13,11,13,29061,2130,True,2,0.04,50,2,83,2,10,0.1724137931034483,18,18
+locoL_fullsat_s40000_K1000,DC,welch_top50_deg,5563,,,,,11,13,11,13,4328,331,True,1,0.07142857142857142,7,8,7,8,5,0.25,18,18

paper-releases/pbisc-diffusion/updates/20261003T103040Z-crosscohort-k1000-saturation/diffusion/dataset/server_1/model8/plans/paired_crosscohort_20261002/scores/giroux2022/locoL_fullsat_s40000_K1000/per_donor.csv

@@ -0,0 +1,25 @@
+arm,donor,group,n_generated_cells,n_observed_cells,n_reference_cells,gen_T cell,obs_T cell,gen_B cell,obs_B cell,gen_Monocyte,obs_Monocyte,gen_NK cell,obs_NK cell,gen_DC,obs_DC,gen_Other,obs_Other,comp_l1,comp_l1_obs_loo_null,pb_r,pb_own_rank,pb_top1,precision,coverage,precision_depth_matched,coverage_depth_matched,mono_pct_gen,mono_pct_obs,median_umi_gen,median_umi_obs
+locoL_fullsat_s40000_K1000,450905_d0,mild,1500,5914,150,0.9213333333333333,0.30943523841731485,0.013333333333333334,0.036185322962461956,0.011333333333333334,0.4293202570172472,0.03333333333333333,0.12089956036523504,0.011333333333333334,0.009976327358809604,0.009333333333333334,0.09418329387893135,1.2265102017810845,0.6266504923198378,0.8462555212757552,23,False,0.9933333333333333,0.5133333333333333,0.9266666666666666,0.5533333333333333,1.1333333333333333,42.93202570172472,502.0,574.5
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+locoL_fullsat_s40000_K1000,0B943B_d0,mild,1500,11344,150,0.8346666666666667,0.6220028208744711,0.08666666666666667,0.08312764456981664,0.030666666666666665,0.12588152327221439,0.030666666666666665,0.11865303244005641,0.008666666666666666,0.023977433004231313,0.008666666666666666,0.026357545839210156,0.4324057357780912,0.1791278384873501,0.8574492689839153,16,False,0.9933333333333333,0.7466666666666667,0.9666666666666667,0.82,3.0666666666666664,12.588152327221438,417.0,539.0
+locoL_fullsat_s40000_K1000,0B943B_d14,mild,1500,15650,150,0.6606666666666666,0.5652396166134185,0.124,0.11175718849840256,0.132,0.17086261980830672,0.052,0.09789137380191694,0.02,0.009968051118210863,0.011333333333333334,0.04428115015974441,0.2354036208732694,0.10063602424453227,0.8943628251688951,2,False,0.9866666666666667,0.78,0.94,0.7666666666666667,13.200000000000001,17.08626198083067,582.5,461.0
+locoL_fullsat_s40000_K1000,7085CA_d0,mild,1500,12585,150,0.6646666666666666,0.21660707191100517,0.048,0.024791418355184745,0.174,0.5874453714739769,0.08133333333333333,0.13198251887167262,0.03,0.017719507350019866,0.002,0.021454112038140644,0.9670973381009137,0.8829287440863147,0.8884807391822479,1,True,0.9866666666666667,0.6866666666666666,0.9266666666666666,0.7466666666666667,17.4,58.74453714739769,574.0,640.0
+locoL_fullsat_s40000_K1000,7085CA_d7,mild,1500,9515,150,0.6886666666666666,0.521492380451918,0.076,0.0722017866526537,0.050666666666666665,0.10110352075669994,0.164,0.2725170782974251,0.014666666666666666,0.019863373620599055,0.006,0.012821860220704152,0.3419449991241898,0.3632282731474772,0.8523668922854712,5,False,0.9933333333333333,0.86,0.92,0.7466666666666667,5.066666666666666,10.110352075669994,366.5,502.0
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+locoL_fullsat_s40000_K1000,2AD75E_d0,mild,1500,7693,150,0.7553333333333333,0.6034056934875861,0.09333333333333334,0.06408423241908229,0.027333333333333334,0.14064734173924348,0.1,0.15949564539191471,0.008,0.025347718705316522,0.016,0.007019368256856883,0.38031474500628276,0.20681142084856263,0.8544325529974238,3,False,0.9933333333333333,0.7666666666666667,0.9533333333333334,0.7533333333333333,2.7333333333333334,14.064734173924348,396.0,532.0
+locoL_fullsat_s40000_K1000,2AD75E_d7,mild,1500,10499,150,0.436,0.5808172206876845,0.29933333333333334,0.14372797409277074,0.11133333333333334,0.10277169254214687,0.09,0.14715687208305553,0.016666666666666666,0.013715591961139155,0.04666666666666667,0.011810648633203162,0.4039481855414801,0.27874882058987843,0.8386085695128119,6,False,1.0,0.8533333333333334,0.9666666666666667,0.76,11.133333333333335,10.277169254214687,281.0,443.0
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+locoL_fullsat_s40000_K1000,180E1A_d7,severe,1500,10591,150,0.8986666666666666,0.7348692285903126,0.038,0.04909829100179398,0.006666666666666667,0.09064299877254273,0.046,0.08280615617033331,0.0006666666666666666,0.010480596733075253,0.01,0.03210272873194221,0.32759487615270816,0.37628768415060193,0.8457763832827252,1,True,0.9933333333333333,0.78,0.9533333333333334,0.7733333333333333,0.6666666666666667,9.064299877254273,392.0,408.0
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