Upload OligoTox_Phase2_Optional_Analysis_Notebook.ipynb
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OligoTox_Phase2_Optional_Analysis_Notebook.ipynb
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"name": "stdout",
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"source": [
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"from pathlib import Path\n",
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"\n",
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"def display_output_path(path):\n",
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" \"\"\"Return a submission-safe relative path for generated notebook outputs.\"\"\"\n",
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" return r\"\\\\notebook_outputs\\\\\" + p.name\n",
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"import json\n",
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"import os\n",
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"import warnings\n",
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"\n",
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"import numpy as np\n",
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"pd.set_option(\"display.max_columns\", 120)\n",
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"pd.set_option(\"display.max_colwidth\", 160)\n",
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"#
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"required_files = [\n",
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" \"oligos.csv\",\n",
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" path = OUTPUT_DIR / name\n",
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" plt.savefig(path, dpi=160, bbox_inches=\"tight\")\n",
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"\n",
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"# Label distribution.\n",
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"label_counts = readouts[\"hepatotoxicity_label\"].value_counts().reindex([\"low\", \"moderate\", \"high\"])\n",
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"source": [
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"## 13. How this notebook supports the optional documentation package\n",
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"\n",
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"This notebook is useful as an optional supplement because it demonstrates four things
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"\n",
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"1. **Ability to solve the challenge:** the dataset can be loaded, joined, modeled, and used for immediate in silico toxicity-label prediction experiments. \n",
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"2. **Potential impact:** the source corpus, evidence modules, and information-gap map show how the dataset addresses gaps across oligo modality, chemistry, dose/exposure, liver context, and readout structure. \n",
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"3. **Feasibility and rigor:** the schema, validation summary, relationship checks, and reproducibility manifest make the package inspectable rather than opaque. \n",
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"4. **Transparency and reproducibility:** the notebook uses only the released files, stores derived artifacts locally, and avoids hidden inputs.\n",
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"\n",
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"The notebook should be presented as optional
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]
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}
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],
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Using dataset folder: C:\\Users\\karto\\NIH-OligoTox Phase II\\dataset_root\n",
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"Notebook outputs will be written to: C:\\Users\\karto\\NIH-OligoTox Phase II\\dataset_root\\notebook_outputs\n"
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]
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}
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],
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"source": [
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"from pathlib import Path\n",
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"import json\n",
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"import os\n",
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"import sys\n",
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"import warnings\n",
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"\n",
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"import numpy as np\n",
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"pd.set_option(\"display.max_columns\", 120)\n",
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"pd.set_option(\"display.max_colwidth\", 160)\n",
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"\n",
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"# Detect Google Colab / cloud environments where the dataset is not in the\n",
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"# current working directory, and auto-download from Hugging Face if so.\n",
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"def locate_dataset():\n",
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" cwd = Path.cwd().resolve()\n",
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" if (cwd / \"oligos.csv\").exists() and (cwd / \"toxicity_readouts.csv\").exists():\n",
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" return cwd\n",
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" is_colab = \"google.colab\" in sys.modules or \"COLAB_GPU\" in os.environ or \"COLAB_RELEASE_TAG\" in os.environ\n",
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" if is_colab or not (cwd / \"oligos.csv\").exists():\n",
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" try:\n",
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" from huggingface_hub import snapshot_download\n",
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" except ImportError:\n",
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" print(\"Installing huggingface_hub for dataset download...\")\n",
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" os.system(f\"{sys.executable} -m pip install --quiet huggingface_hub\")\n",
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" from huggingface_hub import snapshot_download\n",
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" print(\"Downloading dataset from Hugging Face: DBbun/oligotox-phase2-dataset ...\")\n",
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" local_dir = Path(snapshot_download(\n",
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" repo_id=\"DBbun/oligotox-phase2-dataset\",\n",
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" repo_type=\"dataset\",\n",
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" )).resolve()\n",
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" return local_dir\n",
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" return cwd\n",
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"\n",
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"DATA_DIR = locate_dataset()\n",
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"\n",
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"required_files = [\n",
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" \"oligos.csv\",\n",
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"\n",
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"if missing_files:\n",
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" raise FileNotFoundError(\n",
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" \"Could not locate dataset files. To run this notebook, either: \"\n",
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" \"(1) run from a folder containing the dataset CSVs, or \"\n",
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" \"(2) ensure huggingface_hub is installed so the dataset can be auto-downloaded. \"\n",
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" f\"Missing required file(s): {missing_files}\"\n",
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" )\n",
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"\n",
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"OUTPUT_DIR = Path.cwd() / \"notebook_outputs\"\n",
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"OUTPUT_DIR.mkdir(exist_ok=True)\n",
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"\n",
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"# Helper for cleanly displaying file paths in cell outputs\n",
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"def display_output_path(p):\n",
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" try:\n",
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" return str(Path(p).relative_to(Path.cwd()))\n",
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" except ValueError:\n",
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" return str(p)\n",
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"\n",
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"print(f\"Using dataset folder: {DATA_DIR}\")\n",
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"print(f\"Notebook outputs will be written to: {OUTPUT_DIR}\")\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Saved: C:\\Users\\karto\\NIH-OligoTox Phase II\\dataset_root\\notebook_outputs\\notebook_label_distribution.png\n"
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]
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},
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{
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" path = OUTPUT_DIR / name\n",
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" plt.tight_layout()\n",
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" plt.savefig(path, dpi=160, bbox_inches=\"tight\")\n",
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" print(f\"Saved: {path}\")\n",
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"\n",
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"# Label distribution.\n",
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"label_counts = readouts[\"hepatotoxicity_label\"].value_counts().reindex([\"low\", \"moderate\", \"high\"])\n",
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Saved: C:\\Users\\karto\\NIH-OligoTox Phase II\\dataset_root\\notebook_outputs\\notebook_risk_score_distribution_by_label.png\n"
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"text": [
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"text": [
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"Saved: C:\\Users\\karto\\NIH-OligoTox Phase II\\dataset_root\\notebook_outputs\\notebook_median_risk_over_time.png\n"
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"text": [
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"output_type": "stream",
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"text": [
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"text": [
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"Saved: C:\\Users\\karto\\NIH-OligoTox Phase II\\dataset_root\\notebook_outputs\\notebook_risk_vs_GC_content.png\n"
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"output_type": "stream",
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"text": [
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]
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},
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{
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"source": [
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"## 13. How this notebook supports the optional documentation package\n",
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"\n",
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"This notebook is useful as an optional supplement because it demonstrates four things reviewers often care about:\n",
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"\n",
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"1. **Ability to solve the challenge:** the dataset can be loaded, joined, modeled, and used for immediate in silico toxicity-label prediction experiments. \n",
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"2. **Potential impact:** the source corpus, evidence modules, and information-gap map show how the dataset addresses gaps across oligo modality, chemistry, dose/exposure, liver context, and readout structure. \n",
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"3. **Feasibility and rigor:** the schema, validation summary, relationship checks, and reproducibility manifest make the package inspectable rather than opaque. \n",
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"4. **Transparency and reproducibility:** the notebook uses only the released files, stores derived artifacts locally, and avoids hidden inputs.\n",
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"\n",
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"The notebook should be presented as optional reviewer support, not as a substitute for the dataset, schema, data dictionary, validation files, or source/provenance documentation."
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]
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}
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],
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