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Lucas CamilloLucas Camillo
Lucas Camillo
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Lucas Camillo
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updated docs
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‎clocks/notebooks/zhangblup.ipynb

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"cell_type": "code",
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"id": "4adfb4de-cd79-4913-a1af-9e23e9e236c9",
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"import os\n",
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"cell_type": "code",
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"id": "8aa77372-7ed3-4da7-abc9-d30372106139",
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"cell_type": "code",
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"id": "78536494-f1d9-44de-8583-c89a310d2307",
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"metadata": {},
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"outputs": [],
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"source": [
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"model = pya.models.ZhangBLUP()"
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"cell_type": "code",
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"execution_count": 4,
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"id": "6601da9e-8adc-44ee-9308-75e3cd31b816",
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"execution": {
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"iopub.execute_input": "2024-01-21T18:59:44.524665Z",
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"metadata": {},
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"outputs": [],
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"source": [
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"model.metadata[\"clock_name\"] = 'zhangblup'\n",
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"model.metadata[\"data_type\"] = 'methylation'\n",
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"model.metadata[\"species\"] = 'Homo sapiens'\n",
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"model.metadata[\"year\"] = 2023\n",
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"model.metadata[\"year\"] = 2019\n",
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"model.metadata[\"approved_by_author\"] = '⌛'\n",
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"model.metadata[\"citation\"] = \"citation\"\n",
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"model.metadata[\"doi\"] = 'doi'\n",
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"model.metadata[\"citation\"] = \"Zhang, Qian, et al. \\\"Improved precision of epigenetic clock estimates across tissues and its implication for biological ageing.\\\" Genome medicine 11 (2019): 1-11.\"\n",
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"model.metadata[\"doi\"] = 'https://doi.org/10.1186/s13073-019-0667-1'\n",
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"model.metadata[\"notes\"] = None"
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]
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},
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"cell_type": "code",
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"id": "0ee560a3-8ab6-4202-b8b2-cebf75089bfb",
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"id": "8a3d5de6-6303-487a-8b4d-e6345792f7be",
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"metadata": {},
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"outputs": [],
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"source": [
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"df = pd.read_table('DNAm-based-age-predictor/blup.coef', sep=' ')\n",
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"metadata": {},
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"weights = torch.tensor(df['coefficient'][1:].tolist()).unsqueeze(0)\n",
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"metadata": {},
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"base_model = pya.models.LinearModel(input_dim=len(model.features))\n",
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"metadata": {},
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"reference_feature_values_df = pd.read_csv('example_data.csv', index_col=0)\n",
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"model.preprocess_name = 'scale_row'\n",
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"model.postprocess_name = None\n",
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"\n",
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"training: True\n",
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"metadata: {'approved_by_author': '⌛',\n",
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" 'citation': 'citation',\n",
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" 'citation': 'Zhang, Qian, et al. \"Improved precision of epigenetic clock '\n",
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" 'estimates across tissues and its implication for biological '\n",
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" 'ageing.\" Genome medicine 11 (2019): 1-11.',\n",
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" 'clock_name': 'zhangblup',\n",
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" 'data_type': 'methylation',\n",
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" 'doi': 'https://doi.org/10.1186/s13073-019-0667-1',\n",
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" 'species': 'Homo sapiens',\n",
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" 'version': None,\n",
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" 'year': 2023}\n",
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" 'year': 2019}\n",
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"reference_values: [0.05946290980445651, 0.9016779859564634, 0.8511621554128406, 0.07497523935546724, 0.08079601941558237, 0.13789119095690058, 0.959990162673912, 0.054840405638908254, 0.11271586156940745, 0.06867464793155438, 0.04092332774669377, 0.03122014881875939, 0.12091171597794977, 0.8626077673429406, 0.02002095456899887, 0.037161243530447204, 0.5228131230887364, 0.025038065219011623, 0.03411737762225109, 0.023966201717807785, 0.13213191286915785, 0.03613520841142101, 0.11053625925027737, 0.09303164766153527, 0.07697707482010466, 0.040677518106921974, 0.016422537053260692, 0.01646509240082735, 0.9634930275356334, 0.8664078943468241]... [Total elements: 319607]\n",
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"preprocess_name: 'scale_row'\n",
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"preprocess_dependencies: None\n",
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"metadata": {},
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"torch.save(model, f\"../weights/{model.metadata['clock_name']}.pt\")"
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"Deleted file: download.r\n",
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"Deleted folder: .ipynb_checkpoints\n",
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"Deleted folder: DNAm-based-age-predictor\n",
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"Deleted file: example_data.csv\n"
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]

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