# CDPpy

CDPpy (Cell-culture Data Pipeline Python package) is an open-source library designed to analyze fed-batch cell culture data from multiple experiments and cell lines. The package features the functions of a data processing pipeline and visualization toolbox. The processing pipeline reads raw data from Excel files following a fixed template, derives variables such as cumulative substrate consumption and various specific rates, and exports the processed dataset into an Excel file. The particular rates show changing cellular activities in culture over time, providing process optimization insights. The visualization toolbox enables users to analyze process profiles across experimental runs and cell lines, aiding in future experimental design. In this repository, we include the source code for the package, an instruction for package setup, and a Jupyter notebook that provides step-by-step guidelines for data processing and visualization using an example dataset.

## GitHub Repository

https://github.com/ddolab/CDPpy

Future version will be announced in GitHub.

### Developer

- Yen-An Lu (lu000285@umn.edu), Department of Chemical Engineering and Materials Science, University of Minnesota
- Yudai Fukae (fukae001@umn.edu), Department of Biomedical Engineering, University of Minnesota
- Prof. Wei-Shou Hu, Department of Chemical Engineering and Materials Science, University of Minnesota
- Prof. Qi Zhang, Department of Chemical Engineering and Materials Science, University of Minnesota

## Package download instructions

1. Download from DRUM.

- Download and unzip the CDPpy-main.zip under the desired location
- Read the following instruction for package setup and usage guideline

2. Download from GitHub

- Run `git clone https://github.com/ddolab/CDPpy` under desired location
` Read the following instruction for package setup and usage guideline


## Requirements/Package setup

Dependencies can be found in the `environment.yml` file.

To recreate the same Python conda environments, run `conda env create -f environment.yml` in the command prompt.

## Input Excel template

The package reads the data from Excel files following a fixed template. An template (`Package_input_Template.xlsx`) is provided in the `input_files` folder

## User instructions

The Jupyter notebook `Package_tutorial.ipynb` provides a tutorial designed for running on Google Colab. An example dataset, `Package_input_Example.xlsx`, is provided in the `input_files` folder.

A PDF instruction on how to execute the notebook on Google Colab can be found in `Tutorial_Jupyter_notebook_instruction.pdf`.