Sync organagemortalityconventional

README.md

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+---
+license: other
+license_name: original-author-license
+license_link: https://huggingface.co/pyaging/organagemortalityconventional/blob/main/organagemortalityconventional.LICENSE.txt
+library_name: pyaging
+tags:
+- pyaging
+- aging-clock
+- biology
+- proteomics
+---
+
+# organagemortalityconventional
+
+Conventional OrganAge mortality model for Olink Explore 3072, using author-recommended fold 1. Trained on UK Biobank plasma measured with Olink Explore 3072. Input columns are original case-sensitive protein symbols (e.g. NTproBNP, HLA-DRA), not UniProt IDs or Olink assay IDs. Values are assay-normalized Olink NPX on the log2 relative-abundance scale, not raw counts, concentrations, linear abundances or z-scores. No additional centering or cohort scaling is applied. Absent proteins contribute zero; NaNs in supplied proteins propagate, matching the original Example_Script.R scoring expressions. For other assays, the authors recommend a symmetric abundance distribution, protein-wise mean subtraction and SD division, then multiplication by the full-model UKB protein SDs in Table S3. This cohort-dependent cross-platform preparation is not performed by pyaging. The optional Example_Script.R SD-matching step is also external; NPX labeling alone does not establish comparability across Olink panels, batches, plasma and serum. Output is relative natural-log mortality hazard, not age in years. The 2026 Insilico trial used conventional OrganAge models on Olink Explore 3072 serum; organ-specific variants are not the six-clock comparison endpoints. pyaging returns the original raw score and does not apply the trial wrapper's cohort harmonization or mortality-to-years conversion. Models labelled Female and Male contain protein features; neither requires a sex covariate. Academic/non-commercial research use only; commercial use requires a separate license from the authors.
+
+Model weights retain the original authors' terms; the pyaging software license does not relicense them. See the [original author license](organagemortalityconventional.LICENSE.txt). These weights are restricted to research use under the authors' terms.
+
+| | |
+|---|---|
+| **Predicts** | mortality risk |
+| **Species** | Homo sapiens |
+| **Tissue** | plasma |
+| **Data type** | proteomics |
+| **Model type** | elastic net Cox regression |
+| **Year** | 2025 |
+
+## Use with pyaging
+
+```python
+import pyaging as pya
+
+pya.pred.predict_age(adata, ["organagemortalityconventional"])
+```
+
+Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io).
+
+## Citation
+
+Goeminne, L. J. E., et al. "Plasma protein-based organ-specific aging and mortality models unveil diseases as accelerated aging of organismal systems." Cell Metabolism 37, 205–222.e6 (2025).
+
+https://doi.org/10.1016/j.cmet.2024.10.005

config.json

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+{
+ "approved_by_author": "\u231b",
+ "citation": "Goeminne, L. J. E., et al. \"Plasma protein-based organ-specific aging and mortality models unveil diseases as accelerated aging of organismal systems.\" Cell Metabolism 37, 205\u2013222.e6 (2025).",
+ "citations": 128,
+ "citations_date": "2026-10-02",
+ "clock_name": "organagemortalityconventional",
+ "data_type": "proteomics",
+ "doi": "https://doi.org/10.1016/j.cmet.2024.10.005",
+ "journal": "Cell Metabolism",
+ "last_author": "Vadim N. Gladyshev",
+ "model_type": "elastic net Cox regression",
+ "n_features": 2916,
+ "notes": "Conventional OrganAge mortality model for Olink Explore 3072, using author-recommended fold 1. Trained on UK Biobank plasma measured with Olink Explore 3072. Input columns are original case-sensitive protein symbols (e.g. NTproBNP, HLA-DRA), not UniProt IDs or Olink assay IDs. Values are assay-normalized Olink NPX on the log2 relative-abundance scale, not raw counts, concentrations, linear abundances or z-scores. No additional centering or cohort scaling is applied. Absent proteins contribute zero; NaNs in supplied proteins propagate, matching the original Example_Script.R scoring expressions. For other assays, the authors recommend a symmetric abundance distribution, protein-wise mean subtraction and SD division, then multiplication by the full-model UKB protein SDs in Table S3. This cohort-dependent cross-platform preparation is not performed by pyaging. The optional Example_Script.R SD-matching step is also external; NPX labeling alone does not establish comparability across Olink panels, batches, plasma and serum. Output is relative natural-log mortality hazard, not age in years. The 2026 Insilico trial used conventional OrganAge models on Olink Explore 3072 serum; organ-specific variants are not the six-clock comparison endpoints. pyaging returns the original raw score and does not apply the trial wrapper's cohort harmonization or mortality-to-years conversion. Models labelled Female and Male contain protein features; neither requires a sex covariate. Academic/non-commercial research use only; commercial use requires a separate license from the authors.",
+ "platform": [
+  "Olink Explore 3072"
+ ],
+ "population": "adults",
+ "predicts": [
+  "mortality risk"
+ ],
+ "reference_values": true,
+ "research_only": true,
+ "species": "Homo sapiens",
+ "tissue": [
+  "plasma"
+ ],
+ "training_target": [
+  "mortality"
+ ],
+ "unit": [
+  "log hazard"
+ ],
+ "version": "0.5.5",
+ "year": 2025
+}

organagemortalityconventional.LICENSE.txt

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+(Academic / Non-Commercial License)
+
+Copyright (c) 2025
+Ludger J.E. Goeminne and Vadim N. Gladyshev
+
+This software and its associated files (the “Software”) are licensed under a dual-license model:
+
+Academic / Non-Commercial License (this license)
+Commercial License (available separately)
+Permission is hereby granted, free of charge, to any individual or institution, to use, copy, modify, and distribute the Software solely for non-commercial academic or research purposes, subject to the following conditions:
+
+1. Non-Commercial Use Only
+The Software may not be used, in whole or in part, for any commercial purpose. Commercial purposes include, but are not limited to:
+
+Use in a commercial product or service
+Use by a for-profit entity for internal research or development
+Use to generate revenue, directly or indirectly
+Use in regulatory submissions or clinical decision support systems
+
+2. Attribution
+Any academic or research use of the Software must include appropriate citation of the following publication:
+
+Ludger J.E. Goeminne, Anastasiya Vladimirova, Alec Eames, Alexander Tyshkovskiy,
+M. Austin Argentieri, Kejun Ying, Mahdi Moqri, Vadim N. Gladyshev (2025).
+Plasma protein-based organ-specific aging and mortality models unveil diseases as accelerated aging of organismal systems,
+Cell Metabolism, Volume 37, Issue 1, p205–222.e6.
+DOI: https://doi.org/10.1016/j.cmet.2024.10.005
+
+3. No Warranty
+THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, AND NON-INFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES, OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT, OR OTHERWISE, ARISING FROM, OUT OF, OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+
+4. Third-Party Software
+The Software depends on third-party packages that are licensed under their own respective licenses. This license applies only to the original portions of the Software and does not override or modify the terms of any third-party licenses, including but not limited to GPL-licensed components.
+
+5. Commercial Licensing
+Any commercial use of the Software requires a separate commercial license. Interested parties should contact the copyright holders or their institutional technology transfer office to negotiate commercial licensing terms.

organagemortalityconventional.provenance.json

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+{
+  "repository": "https://github.com/ludgergoeminne/organAging",
+  "commit": "5147b0301ec7f4abdb10ef650d04f47454ddc8fd",
+  "coefficient_path": "data/output_Python/instance_0/mortality_based_models/Conventional_mortality_coefs_GTEx_4x_FC.csv",
+  "coefficient_sha256": "2beb67bc593a86e6e5e9aec98c2b1c23bd84b18ea3e032d71310d1278e65889e",
+  "prediction_code_path": "scripts/R/Example_Script.R",
+  "prediction_code_sha256": "02fc291721d6018bafa5a49adf4aff3841c7e9d085d682088b9ac0feeee31e63",
+  "fold": 1
+}

organagemortalityconventional.pt

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