🧬 Curation Assistant Tool

A Streamlit app for bioinformatics curation that combines:

• 📄 Document summarization & Q&A (PDF, DOCX, TXT, XLSX)
• 🖼️ Figure extraction from PDFs (with OCR text search)
• 📊 Gene frequency calculation from supplementary tables
• 🔎 Gene lookup across cBioPortal-style files (data_mutations.txt, data_cna.txt, data_sv.txt)

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Quickstart

1. Clone this repo

git clone https://github.com/<your-username>/<your-repo>.git
cd <your-repo>

2. Create environment & install dependencies

python3.10 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

3. Set your OpenAI API key

You’ll need an API key from OpenAI.

export OPENAI_API_KEY="sk-..."

(On Windows PowerShell:)

$env:OPENAI_API_KEY="sk-..."

4. Run the app

streamlit run new_app.py

The app will open in your browser at http://localhost:8501.

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Deployment on Streamlit Cloud

1. Push this repo to GitHub.
2. Go to Streamlit Cloud.
3. Connect your repo and select new_app.py as the app file.
4. Add your OpenAI API key as a Secret in Streamlit Cloud (OPENAI_API_KEY).
5. Deploy — you’ll get a shareable public link like:

https://your-username-your-repo.streamlit.app

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📂 File Structure

your-repo/
├── new_app.py          # Main Streamlit app
├── requirements.txt    # Python dependencies
├── README.md           # This file
├── runtime.txt         # (optional) Python version for Streamlit Cloud
├── apt.txt             # (optional) system packages, e.g. for OCR
└── .streamlit/
    └── config.toml     # (optional) custom Streamlit theme

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Features

• Summarization & Q&A

  • Grounded strictly in uploaded files
  • Supports PDFs, Word, TXT, Excel
  • Cites file name, sheet, and page numbers

• Figure Extraction

  • Extracts embedded images from PDFs
  • OCR text indexing for searchable captions

• Gene Frequencies

  • Upload supplementary tables (.csv/.tsv/.txt/.xlsx)
  • Compute frequencies automatically or with custom denominator
  • Download results as CSV

• Gene Lookup

  • Search for single or multiple genes (e.g., TP53, EGFR, KRAS)
  • Supports Hugo_Symbol in mutation/CNA files
  • Supports Site1_Hugo_Symbol / Site2_Hugo_Symbol in SV files
  • Reports per-file sample counts and percentages

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Requirements

• Python 3.10+
• Internet access (for OpenAI API calls)

Install from requirements.txt:

pip install -r requirements.txt

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🙋 Usage Example

1. Upload your cBioPortal supplementary files:

   • data_mutations.txt
   • data_cna.txt
   • data_sv.txt
   • data_clinical_sample.txt

2. Query genes:

   TP53, EGFR, KRAS
   

3. See sample counts & % frequencies directly in the app.

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👨‍💻 Author

Built by Baby Anusha Satravada · Bioinformatics Software Engineer
Memorial Sloan Kettering Cancer Center (MSK)

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