Archive 4 checkpoints (1-4)
Browse files- paper-releases/pbisc-diffusion/updates/20261008T022410Z-deconv-scsemi-deck/diffusion/dataset/server_1/model8/plans/bayesprism_paired_20261006/logs/aggregates.log +27 -0
- paper-releases/pbisc-diffusion/updates/20261008T022410Z-deconv-scsemi-deck/diffusion/dataset/server_1/model8/plans/bayesprism_paired_20261006/logs/aggregates_full.log +10 -0
- paper-releases/pbisc-diffusion/updates/20261008T022410Z-deconv-scsemi-deck/diffusion/dataset/server_1/model8/plans/bayesprism_paired_20261006/results/RESULTS_cibersortx.md +27 -0
- paper-releases/pbisc-diffusion/updates/20261008T022410Z-deconv-scsemi-deck/diffusion/dataset/server_1/model8/plans/bayesprism_paired_20261006/results/RESULTS_full.md +27 -0
paper-releases/pbisc-diffusion/updates/20261008T022410Z-deconv-scsemi-deck/diffusion/dataset/server_1/model8/plans/bayesprism_paired_20261006/logs/aggregates.log
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{"dataset": "ye2026_sepsis", "cells": 610713, "samples": 85, "states": 29, "genes": 5959, "scoring_genes": 5975, "cells_full": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/ye2026_sepsis/cells_full.npz", "cells_full_sha256": "0b3606b6ab70342eca37c2ac8068d86593774bb921f756db4295b5d1d0a33f3f", "labels": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/ye2026_sepsis/observed_labels/labels/labels.parquet", "labels_sha256": "ab27c027a75b7cd47ec8267d4b33bfe41e8cb6ab64190a3592db1cffa2a73ea7", "aggregates_sha256": "d38afdb00f5616ada109babfb6fc0f16bc37b33a434807d263d0163895e1f9de", "tool_sha256": "1cd3befb81046a3968cb09c0bcc792f7b27d5d00cc9faf5bf691e7af6124139e", "common_sha256": "23599c7dc2bade09c3e0f6a613a4a63670adab6d1d1e8468ef175c89bd6e2ebf", "seconds": 16.9}
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Traceback (most recent call last):
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File "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/bayesprism_paired_20261006/tools/build_aggregates.py", line 83, in <module>
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sys.exit(main())
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^^^^^^
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File "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/bayesprism_paired_20261006/tools/build_aggregates.py", line 43, in main
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lab = pd.read_parquet(lpath, columns=["sample_id", "celltype_l1_pred", "aifi_l2", "npz_row"])
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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File "/home/sj_server_1/miniforge3/envs/cxg_corpus/lib/python3.11/site-packages/pandas/io/parquet.py", line 669, in read_parquet
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return impl.read(
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^^^^^^^^^^
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File "/home/sj_server_1/miniforge3/envs/cxg_corpus/lib/python3.11/site-packages/pandas/io/parquet.py", line 258, in read
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path_or_handle, handles, filesystem = _get_path_or_handle(
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^^^^^^^^^^^^^^^^^^^^
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File "/home/sj_server_1/miniforge3/envs/cxg_corpus/lib/python3.11/site-packages/pandas/io/parquet.py", line 141, in _get_path_or_handle
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handles = get_handle(
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^^^^^^^^^^^
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File "/home/sj_server_1/miniforge3/envs/cxg_corpus/lib/python3.11/site-packages/pandas/io/common.py", line 882, in get_handle
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handle = open(handle, ioargs.mode)
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^^^^^^^^^^^^^^^^^^^^^^^^^
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FileNotFoundError: [Errno 2] No such file or directory: '/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/immicro/observed_labels/labels/labels.parquet'
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FAILED immicro
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{"dataset": "ji2025_chili", "cells": 154698, "samples": 40, "states": 29, "genes": 5736, "scoring_genes": 5752, "cells_full": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/ji2025_chili/cells_full.npz", "cells_full_sha256": "96205f63b2ed3321cae700a28e9f48af4a36e7adc19d1e3307ad42d6475d1e7d", "labels": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/ji2025_chili/observed_labels/labels/labels.parquet", "labels_sha256": "15f939ad216a7bbb08cf65e11809ef90057c4d2e31ad36bf3b3b70b1d5a49ff7", "aggregates_sha256": "ab2d1c650eea9381badef93975c96714399d8f538655888c433321af04663247", "tool_sha256": "1cd3befb81046a3968cb09c0bcc792f7b27d5d00cc9faf5bf691e7af6124139e", "common_sha256": "23599c7dc2bade09c3e0f6a613a4a63670adab6d1d1e8468ef175c89bd6e2ebf", "seconds": 4.9}
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{"dataset": "imperial_eskd", "cells": 534014, "samples": 172, "states": 29, "genes": 5911, "scoring_genes": 5927, "cells_full": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/imperial_eskd/cells_full.npz", "cells_full_sha256": "4629d8cc14d1a6b73f7c5e28847ffce215ad316055b2bde8e90f7ca2a4bd6f67", "labels": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/imperial_eskd/observed_labels/labels/labels.parquet", "labels_sha256": "b7451fb96819132a1b72d739ebe95a78674a764769ee80746975adaed55cf67f", "aggregates_sha256": "80b9c3401d8d4c724088317828a5c5095a5157ebc66d099e8399b6f948e507f8", "tool_sha256": "1cd3befb81046a3968cb09c0bcc792f7b27d5d00cc9faf5bf691e7af6124139e", "common_sha256": "23599c7dc2bade09c3e0f6a613a4a63670adab6d1d1e8468ef175c89bd6e2ebf", "seconds": 16.0}
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{"dataset": "giroux2022", "cells": 276615, "samples": 26, "states": 29, "genes": 5556, "scoring_genes": 5563, "cells_full": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/giroux2022/cells_full.npz", "cells_full_sha256": "44613c8b250fc8a8fe39490ecb0cd7fba308dd67b98ce611c1b5912c9274fc18", "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", "labels_sha256": "7bcd985a9e6b7868c4816d9af4d3f48de9ecf1a1b2bc340fb0c5dc26d7b6fe81", "aggregates_sha256": "9b80e097aafc8e9f46bba6166b50af98391afa05d8584acf7066a697762db5c7", "tool_sha256": "1cd3befb81046a3968cb09c0bcc792f7b27d5d00cc9faf5bf691e7af6124139e", "common_sha256": "23599c7dc2bade09c3e0f6a613a4a63670adab6d1d1e8468ef175c89bd6e2ebf", "seconds": 7.0}
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cells_full row_sample disagrees with cells_obs.parquet sample_id
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{"dataset": "immicro", "cells": 392251, "samples": 107, "states": 29, "genes": 5492, "scoring_genes": 5508, "cells_full": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/immicro/cells_full.npz", "cells_full_sha256": "2f19e3a9c02786df401a8b618bd053eb9274d82e6f017f1967b2e2bed787496b", "labels": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/utility_studies_final6k_20260925/immicro/labels/observed_immicro/labels.parquet", "labels_sha256": "143726fc6ba857943e27144bfaa5beaaf2a93b094af4e1f4fc837f1838ff2bda", "aggregates_sha256": "7b6b34edb120956685ca3bf8081babec375584c1dfc8c8eb3800fb1154fe598f", "tool_sha256": "aa4e650d3cecf14a2c7541b897e3924bd85b365ae96f0417d6f7dfe7b44c64ff", "common_sha256": "23599c7dc2bade09c3e0f6a613a4a63670adab6d1d1e8468ef175c89bd6e2ebf", "seconds": 16.4}
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paper-releases/pbisc-diffusion/updates/20261008T022410Z-deconv-scsemi-deck/diffusion/dataset/server_1/model8/plans/bayesprism_paired_20261006/logs/aggregates_full.log
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{"dataset": "ye2026_sepsis", "cells": 610713, "samples": 85, "states": 29, "genes": 18787, "scoring_genes": 5975, "cells_full": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/ye2026_sepsis/cells_full.npz", "cells_full_sha256": "0b3606b6ab70342eca37c2ac8068d86593774bb921f756db4295b5d1d0a33f3f", "labels": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/ye2026_sepsis/observed_labels/labels/labels.parquet", "labels_sha256": "ab27c027a75b7cd47ec8267d4b33bfe41e8cb6ab64190a3592db1cffa2a73ea7", "gene_mode": "full", "aggregates_sha256": "18902e363fa6c3b4bcaa6ad64ea3d151555eda693b933150ea7a9b031699f55e", "tool_sha256": "d25459ce4b2ef7e3b72a62801b7f1b07373bbe8a58effadcd485629e18b727c1", "common_sha256": "8d114d101ed0e41cf8570144e621310fd38eb24f5e1efcc0756af1d3d4fb918f", "seconds": 27.5}
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{"dataset": "imperial_eskd", "cells": 534014, "samples": 172, "states": 29, "genes": 18599, "scoring_genes": 5927, "cells_full": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/imperial_eskd/cells_full.npz", "cells_full_sha256": "4629d8cc14d1a6b73f7c5e28847ffce215ad316055b2bde8e90f7ca2a4bd6f67", "labels": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/imperial_eskd/observed_labels/labels/labels.parquet", "labels_sha256": "b7451fb96819132a1b72d739ebe95a78674a764769ee80746975adaed55cf67f", "gene_mode": "full", "aggregates_sha256": "7d5fb26c54191691e56bfc7f25aeed97ceba3192b29b8b1ecbbbdf8df993ff83", "tool_sha256": "d25459ce4b2ef7e3b72a62801b7f1b07373bbe8a58effadcd485629e18b727c1", "common_sha256": "8d114d101ed0e41cf8570144e621310fd38eb24f5e1efcc0756af1d3d4fb918f", "seconds": 17.1}
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{"dataset": "immicro", "cells": 392251, "samples": 107, "states": 29, "genes": 15404, "scoring_genes": 5508, "cells_full": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/immicro/cells_full.npz", "cells_full_sha256": "2f19e3a9c02786df401a8b618bd053eb9274d82e6f017f1967b2e2bed787496b", "labels": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/utility_studies_final6k_20260925/immicro/labels/observed_immicro/labels.parquet", "labels_sha256": "143726fc6ba857943e27144bfaa5beaaf2a93b094af4e1f4fc837f1838ff2bda", "gene_mode": "full", "aggregates_sha256": "356731ec6b2340b61938f03a1a381f262d701adf0d66b016a4886c579dccca49", "tool_sha256": "d25459ce4b2ef7e3b72a62801b7f1b07373bbe8a58effadcd485629e18b727c1", "common_sha256": "8d114d101ed0e41cf8570144e621310fd38eb24f5e1efcc0756af1d3d4fb918f", "seconds": 19.3}
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{"dataset": "ji2025_chili", "cells": 154698, "samples": 40, "states": 29, "genes": 18172, "scoring_genes": 5752, "cells_full": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/ji2025_chili/cells_full.npz", "cells_full_sha256": "96205f63b2ed3321cae700a28e9f48af4a36e7adc19d1e3307ad42d6475d1e7d", "labels": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/ji2025_chili/observed_labels/labels/labels.parquet", "labels_sha256": "15f939ad216a7bbb08cf65e11809ef90057c4d2e31ad36bf3b3b70b1d5a49ff7", "gene_mode": "full", "aggregates_sha256": "2465354b6111b48fe80a0560315efffa8396ec5d22e9c0b63c6af520675fca06", "tool_sha256": "d25459ce4b2ef7e3b72a62801b7f1b07373bbe8a58effadcd485629e18b727c1", "common_sha256": "8d114d101ed0e41cf8570144e621310fd38eb24f5e1efcc0756af1d3d4fb918f", "seconds": 6.4}
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{"dataset": "giroux2022", "cells": 276615, "samples": 26, "states": 29, "genes": 17988, "scoring_genes": 5563, "cells_full": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/giroux2022/cells_full.npz", "cells_full_sha256": "44613c8b250fc8a8fe39490ecb0cd7fba308dd67b98ce611c1b5912c9274fc18", "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", "labels_sha256": "7bcd985a9e6b7868c4816d9af4d3f48de9ecf1a1b2bc340fb0c5dc26d7b6fe81", "gene_mode": "full", "aggregates_sha256": "c7d332cc8e56a94d26953f51295bebc629d13e27834c08851abfe648063bad8e", "tool_sha256": "d25459ce4b2ef7e3b72a62801b7f1b07373bbe8a58effadcd485629e18b727c1", "common_sha256": "8d114d101ed0e41cf8570144e621310fd38eb24f5e1efcc0756af1d3d4fb918f", "seconds": 7.0}
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{"dataset": "ye2026_sepsis", "cells": 610713, "samples": 85, "states": 29, "genes": 18787, "scoring_genes": 5975, "cells_full": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/ye2026_sepsis/cells_full.npz", "cells_full_sha256": "0b3606b6ab70342eca37c2ac8068d86593774bb921f756db4295b5d1d0a33f3f", "labels": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/ye2026_sepsis/observed_labels/labels/labels.parquet", "labels_sha256": "ab27c027a75b7cd47ec8267d4b33bfe41e8cb6ab64190a3592db1cffa2a73ea7", "gene_mode": "full", "aggregates_sha256": "1c866cbb8990359c870f46804e55cbae4a38cb82b5e0bf5f47bd9a552ada966a", "tool_sha256": "d25459ce4b2ef7e3b72a62801b7f1b07373bbe8a58effadcd485629e18b727c1", "common_sha256": "6f6e873744fff7d06ff3495b058bdceaa572fce7a932eb0fc6addb74f0711875", "seconds": 23.4}
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{"dataset": "imperial_eskd", "cells": 534014, "samples": 172, "states": 29, "genes": 18599, "scoring_genes": 5927, "cells_full": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/imperial_eskd/cells_full.npz", "cells_full_sha256": "4629d8cc14d1a6b73f7c5e28847ffce215ad316055b2bde8e90f7ca2a4bd6f67", "labels": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/imperial_eskd/observed_labels/labels/labels.parquet", "labels_sha256": "b7451fb96819132a1b72d739ebe95a78674a764769ee80746975adaed55cf67f", "gene_mode": "full", "aggregates_sha256": "681a49cc9eb86b0d8b313bc417eef9b11c122894922181cf17a62765612ad1d4", "tool_sha256": "d25459ce4b2ef7e3b72a62801b7f1b07373bbe8a58effadcd485629e18b727c1", "common_sha256": "6f6e873744fff7d06ff3495b058bdceaa572fce7a932eb0fc6addb74f0711875", "seconds": 21.3}
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{"dataset": "immicro", "cells": 392251, "samples": 107, "states": 29, "genes": 15404, "scoring_genes": 5508, "cells_full": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/immicro/cells_full.npz", "cells_full_sha256": "2f19e3a9c02786df401a8b618bd053eb9274d82e6f017f1967b2e2bed787496b", "labels": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/utility_studies_final6k_20260925/immicro/labels/observed_immicro/labels.parquet", "labels_sha256": "143726fc6ba857943e27144bfaa5beaaf2a93b094af4e1f4fc837f1838ff2bda", "gene_mode": "full", "aggregates_sha256": "4215e1c95c8ff835ea4867157ac47c5ae1b7cc8c51c4f4b5457e4c2e537b9aca", "tool_sha256": "d25459ce4b2ef7e3b72a62801b7f1b07373bbe8a58effadcd485629e18b727c1", "common_sha256": "6f6e873744fff7d06ff3495b058bdceaa572fce7a932eb0fc6addb74f0711875", "seconds": 15.6}
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{"dataset": "ji2025_chili", "cells": 154698, "samples": 40, "states": 29, "genes": 18172, "scoring_genes": 5752, "cells_full": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/ji2025_chili/cells_full.npz", "cells_full_sha256": "96205f63b2ed3321cae700a28e9f48af4a36e7adc19d1e3307ad42d6475d1e7d", "labels": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/scoring_cache/ji2025_chili/observed_labels/labels/labels.parquet", "labels_sha256": "15f939ad216a7bbb08cf65e11809ef90057c4d2e31ad36bf3b3b70b1d5a49ff7", "gene_mode": "full", "aggregates_sha256": "0dfbed64479372c0b0cca489dd54f65c6290d9a89da4f1a09d4accaa7140d35f", "tool_sha256": "d25459ce4b2ef7e3b72a62801b7f1b07373bbe8a58effadcd485629e18b727c1", "common_sha256": "6f6e873744fff7d06ff3495b058bdceaa572fce7a932eb0fc6addb74f0711875", "seconds": 5.1}
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| 10 |
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{"dataset": "giroux2022", "cells": 276615, "samples": 26, "states": 29, "genes": 17988, "scoring_genes": 5563, "cells_full": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/data/giroux2022/cells_full.npz", "cells_full_sha256": "44613c8b250fc8a8fe39490ecb0cd7fba308dd67b98ce611c1b5912c9274fc18", "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", "labels_sha256": "7bcd985a9e6b7868c4816d9af4d3f48de9ecf1a1b2bc340fb0c5dc26d7b6fe81", "gene_mode": "full", "aggregates_sha256": "6c0178da65a0929edf63875236d62080254279829c59603e489edeb64ae86e2f", "tool_sha256": "d25459ce4b2ef7e3b72a62801b7f1b07373bbe8a58effadcd485629e18b727c1", "common_sha256": "6f6e873744fff7d06ff3495b058bdceaa572fce7a932eb0fc6addb74f0711875", "seconds": 7.1}
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paper-releases/pbisc-diffusion/updates/20261008T022410Z-deconv-scsemi-deck/diffusion/dataset/server_1/model8/plans/bayesprism_paired_20261006/results/RESULTS_cibersortx.md
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# CIBERSORTx with the same paired donors vs LoRA (paired benchmark; gene mode cibersortx)
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CIBERSORTx in place of BayesPrism ('BP' columns): official Docker Fractions, single-cell reference (<=400 cells per type from the same paired donors) with S-mode batch correction, then HiRes per-sample cell-type expression on the scoring genes (tools/run_cibersortx.sh). One fraction estimate, so 'final' = 'first'. HiRes needs more samples than cell types: splits with <= 8 test samples (Ji and Giroux CV folds) have composition only.
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Same donors, observed truth, contrast and scorer as the benchmark (score_ft.py functions; the recomputed bulk broadcast equals the stored one in every split). BayesPrism reference = the split's paired donors' observed cells (states = gate | AIFI L2); mixture = the test samples' real bulk. Composition L1 in cell units (lower is better): 'final' and 'first' BayesPrism theta. logFC r = case-vs-control per-type logFC (mean CP10K) correlation with observed, mean of T/B/Mono/NK; BayesPrism Z zero-filled on genes it lacks ('covered' = only genes it models, broadcast recomputed there). DEG = top-50 overlap summed over types.
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## Five-donor draws (mean ± SD over 5 draws)
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| cohort | L1 BP final | L1 BP first | L1 LoRA-5 | r BP | r BP (covered) | r LoRA-5 | r broadcast | partial r BP | partial r LoRA-5 | DEG BP | DEG LoRA-5 | DEG broadcast |
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|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|
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| ImMicro (5) | 0.491 ± 0.095 | 0.491 ± 0.095 | 0.176 ± 0.012 | – | – | – | – | – | – | – | – | – |
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| Sepsis (5) | 0.582 ± 0.024 | 0.582 ± 0.024 | 0.466 ± 0.044 | 0.069 ± 0.023 | 0.106 ± 0.043 | 0.350 ± 0.162 | 0.320 ± 0.024 | -0.010 ± 0.026 | 0.305 ± 0.189 | 25.4 ± 3.4 | 16.4 ± 6.7 | 20.0 ± 1.9 |
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| Ji ChILI (5) | 0.827 ± 0.145 | 0.827 ± 0.145 | 0.513 ± 0.115 | 0.158 ± 0.054 | 0.263 ± 0.071 | 0.333 ± 0.077 | 0.234 ± 0.026 | 0.005 ± 0.046 | 0.300 ± 0.076 | 0.0 ± 0.0 | 0.2 ± 0.4 | 1.0 ± 2.2 |
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| Imperial (5) | 0.646 ± 0.026 | 0.646 ± 0.026 | 0.503 ± 0.022 | 0.283 ± 0.011 | 0.363 ± 0.016 | 0.749 ± 0.024 | 0.656 ± 0.009 | 0.061 ± 0.014 | 0.603 ± 0.033 | 30.8 ± 4.6 | 113.6 ± 6.3 | 74.8 ± 7.7 |
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| Giroux (5) | 0.669 ± 0.124 | 0.669 ± 0.124 | 0.256 ± 0.030 | 0.095 ± 0.050 | 0.201 ± 0.088 | 0.297 ± 0.082 | 0.492 ± 0.085 | 0.029 ± 0.011 | 0.189 ± 0.054 | 0.0 ± 0.0 | 0.2 ± 0.4 | 0.0 ± 0.0 |
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Draws where LoRA-5 beats CIBERSORTx: composition 24/25 (vs CIBERSORTx's better theta), logFC r 17/17, partial r 17/17, top-50 DEG 7/20 (ties 9).
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## 5-fold CV, pooled (CIBERSORTx reference = each fold's LoRA training + inner-validation pairs)
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| 21 |
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| cohort | L1 BP final | L1 BP first | L1 LoRA | L1 scSemi | r BP | r BP (covered) | r LoRA | r scSemi | r broadcast | partial r BP | partial r LoRA | DEG BP | DEG LoRA | DEG scSemi | DEG broadcast |
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|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|
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| ImMicro | 0.507 | 0.507 | 0.162 | 0.217 | – | – | – | – | – | – | – | – | – | – | – |
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+
| Sepsis | 0.607 | 0.607 | 0.362 | 0.502 | -0.036 | -0.125 | 0.527 | 0.435 | 0.316 | -0.074 | 0.469 | 0 | 23 | 6 | 21 |
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| Ji ChILI | 0.914 | 0.914 | 0.504 | 0.575 | – | – | – | 0.273 | – | – | – | – | – | 0 | – |
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| Imperial | 0.592 | 0.592 | 0.376 | – | 0.211 | 0.369 | 0.819 | – | 0.661 | 0.016 | 0.690 | 1 | 143 | – | 84 |
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| Giroux | 0.591 | 0.591 | 0.258 | 0.243 | – | – | – | 0.537 | – | – | – | – | – | 0 | – |
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paper-releases/pbisc-diffusion/updates/20261008T022410Z-deconv-scsemi-deck/diffusion/dataset/server_1/model8/plans/bayesprism_paired_20261006/results/RESULTS_full.md
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# BayesPrism with the same paired donors vs LoRA (paired benchmark; gene mode full)
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| 2 |
+
|
| 3 |
+
BayesPrism genes: its recommended set (canonical protein-coding minus chrX/Y/M and RPS/RPL/MRPS/MRPL, measured by the sc assay; 15-19k genes).
|
| 4 |
+
|
| 5 |
+
Same donors, observed truth, contrast and scorer as the benchmark (score_ft.py functions; the recomputed bulk broadcast equals the stored one in every split). BayesPrism reference = the split's paired donors' observed cells (states = gate | AIFI L2); mixture = the test samples' real bulk. Composition L1 in cell units (lower is better): 'final' and 'first' BayesPrism theta. logFC r = case-vs-control per-type logFC (mean CP10K) correlation with observed, mean of T/B/Mono/NK; BayesPrism Z zero-filled on genes it lacks ('covered' = only genes it models, broadcast recomputed there). DEG = top-50 overlap summed over types.
|
| 6 |
+
|
| 7 |
+
## Five-donor draws (mean ± SD over 5 draws)
|
| 8 |
+
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| 9 |
+
| cohort | L1 BP final | L1 BP first | L1 LoRA-5 | r BP | r BP (covered) | r LoRA-5 | r broadcast | partial r BP | partial r LoRA-5 | DEG BP | DEG LoRA-5 | DEG broadcast |
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| 10 |
+
|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|
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| 11 |
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| ImMicro (5) | 0.594 ± 0.088 | 0.550 ± 0.164 | 0.176 ± 0.012 | – | – | – | – | – | – | – | – | – |
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| 12 |
+
| Sepsis (5) | 0.643 ± 0.118 | 0.543 ± 0.218 | 0.466 ± 0.044 | 0.241 ± 0.035 | 0.258 ± 0.036 | 0.350 ± 0.162 | 0.320 ± 0.024 | 0.095 ± 0.035 | 0.305 ± 0.189 | 27.0 ± 2.0 | 16.4 ± 6.7 | 20.0 ± 1.9 |
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| 13 |
+
| Ji ChILI (5) | 0.943 ± 0.117 | 0.952 ± 0.161 | 0.513 ± 0.115 | 0.193 ± 0.013 | 0.212 ± 0.013 | 0.333 ± 0.077 | 0.234 ± 0.026 | 0.032 ± 0.020 | 0.300 ± 0.076 | 2.0 ± 2.4 | 0.2 ± 0.4 | 1.0 ± 2.2 |
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| 14 |
+
| Imperial (5) | 0.962 ± 0.086 | 0.845 ± 0.063 | 0.503 ± 0.022 | 0.598 ± 0.033 | 0.614 ± 0.034 | 0.749 ± 0.024 | 0.656 ± 0.009 | 0.187 ± 0.039 | 0.603 ± 0.033 | 72.4 ± 10.1 | 113.6 ± 6.3 | 74.8 ± 7.7 |
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| 15 |
+
| Giroux (5) | 1.807 ± 0.047 | 1.455 ± 0.361 | 0.256 ± 0.030 | 0.371 ± 0.060 | 0.374 ± 0.060 | 0.297 ± 0.082 | 0.492 ± 0.085 | 0.117 ± 0.060 | 0.189 ± 0.054 | 0.2 ± 0.4 | 0.2 ± 0.4 | 0.0 ± 0.0 |
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| 16 |
+
|
| 17 |
+
Draws where LoRA-5 beats BayesPrism: composition 22/25 (vs BayesPrism's better theta), logFC r 15/20, partial r 18/20, top-50 DEG 6/20 (ties 6).
|
| 18 |
+
|
| 19 |
+
## 5-fold CV, pooled (BayesPrism reference = each fold's LoRA training + inner-validation pairs)
|
| 20 |
+
|
| 21 |
+
| cohort | L1 BP final | L1 BP first | L1 LoRA | L1 scSemi | r BP | r BP (covered) | r LoRA | r scSemi | r broadcast | partial r BP | partial r LoRA | DEG BP | DEG LoRA | DEG scSemi | DEG broadcast |
|
| 22 |
+
|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|
|
| 23 |
+
| ImMicro | 0.575 | 0.909 | 0.162 | 0.217 | – | – | – | – | – | – | – | – | – | – | – |
|
| 24 |
+
| Sepsis | 0.603 | 0.475 | 0.362 | 0.502 | 0.255 | 0.253 | 0.527 | 0.435 | 0.316 | 0.095 | 0.469 | 37 | 23 | 6 | 21 |
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| 25 |
+
| Ji ChILI | 0.883 | 1.055 | 0.504 | 0.575 | 0.186 | 0.204 | 0.479 | 0.273 | 0.240 | 0.020 | 0.452 | 4 | 15 | 0 | 4 |
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| 26 |
+
| Imperial | 0.887 | 1.022 | 0.376 | – | 0.568 | 0.584 | 0.819 | – | 0.661 | 0.112 | 0.690 | 91 | 143 | – | 84 |
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| 27 |
+
| Giroux | 1.803 | 0.878 | 0.258 | 0.243 | 0.406 | 0.408 | 0.461 | 0.537 | 0.575 | 0.022 | 0.323 | 3 | 5 | 0 | 5 |
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