deepNGS Navigator Panel Application

Getting Started

1. Environment Setup

Set up the required environment by creating a new Conda environment using the provided environment.yml file:

conda env create -f environment.yml

2. Input Dataset

The application requires the output of deepNGS mappings with the following minimum required columns:

• e1 and e2: Two-dimensional embeddings used for visualization.
• AA: Sequence information that will be used by the panel application to draw MSAs.
• picked_clones: A string identifying clones of interest (e.g., binders). If no such clones are identified, this column can be left null.

Additional Columns:

Other columns in the dataset can be used for point size and color annotations.

Setting Up Input Files:

To integrate input files into the panel application, include their paths and metadata in the processed_files.csv table. This file should contain the following columns:

• name: A string identifier for the project. Use the format XXX:YYY if you want several subprojects (e.g., YYY) grouped under a main project (e.g., XXX) in the panel menu.
• path: The file path to the dataset corresponding to the project or subproject.

3. Run the Panel Application

Start the panel application using the following command:

panel serve main.py --port 5018

4. Using the Application

Once the panel application is running:

1. Copy the HTTP address provided in the terminal into your web browser.

2. In the browser interface:

   • Select the desired project from the menu.
   • Choose options for point size and color.
   • Press the Display Map button.

3. After the map is displayed:

   • Use the zoom controls to explore different parts of the map.
   • Use lasso or box select tools to select sequences of interest.
   • View their MSA patterns.
   • If needed, download the selected sequences directly from the interface.

License

This software is licensed under a modified Apache License, Version 2.0 (the "License"), specifically a Genentech Non-Commercial Software License. You may not use these files except in compliance with the License. You may obtain a copy of the License.

Unless required by applicable law or agreed upon in writing, software distributed under the License is provided on an "as is" basis, without warranties or conditions of any kind, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Citation

If you use this code, please cite:

@article {MohammadiPeyhani2025.01.27.634805,
   title = {deepNGS Navigator: Exploring antibody NGS datasets using deep contrastive learning},
	author = {MohammadiPeyhani, Homa and Lee, Edith and Bonneau, Richard and Gligorijevic, Vladimir and Lee, Jae Hyeon},
	year = {2025},
	doi = {10.1101/2025.01.27.634805},
	URL = {https://www.biorxiv.org/content/early/2025/01/28/2025.01.27.634805},
	eprint = {https://www.biorxiv.org/content/early/2025/01/28/2025.01.27.634805.full.pdf},
	journal = {bioRxiv}
}