FETCH-PY

The FETCH-PY repository contains scripts and tools to automate the FETCH (Fluorescence Expression Through Cell Harvesting) analysis process for FCS (Flow Cytometry Standard) data files.

Summary

This repository aims to streamline the analysis workflow, which includes quality data checks, applying various gating procedures, and calculating the FETCH score. The automation supports contour-based gating, standard deviation gating, and quadrant gating. The final FETCH score is saved to a CSV file, and potential issues with data integrity are flagged. The repository also includes options for generating PDF outputs of the gating steps to assist in debugging and result verification.

Installation

clone repository

git clone https://github.com/shahinrahimi/FETCH-PY.git
cd FETCH-PY

create environment

conda env create -n fetchenv --file fetchenv.yml

activate environment

conda activate fetchenv

Usage

To run the pipeline, use the following command:

python main.py -f <target_folder> -e <skip_files> -w <overwrite>

• -f or --folder: Path to the folder containing .fcs files for analysis (default is example).
• -e or --skip-files: List of .fcs files to skip (optional).
• -w or --overwrite: Whether to overwrite existing results (default is True).

Example

python main.py -f example -e skip1.fcs skip2.fcs -w True

Parameters

Biexponential Transformation Parameters

The pipeline uses a biexponential transformation for data processing. You can adjust the following parameters in the Config class:

class Config:
  width_multi: int = 0.00001
  pos: float = 4.418540
  neg: float = 0.5

• width_multi: The width of the linear region of the transformation. Controls the smoothness of the transition between linear and logarithmic regions. Default is 0.00001.
• pos: The positive minimum value for the transformation. Defines where the transition to the linear region starts. Default is 4.418540.
• neg: The negative minimum value for the transformation. Sets the minimum threshold for negative values. Default is 0.5.