PanR 0.1.0

A Python tool for panresistome analysis

PanR: Panresistome Analysis Tool

Overview

PanR is a Python-based tool for analyzing panresistome data. It processes NCBI and Abricate summary files, merges the data, and generates visualizations such as lollipop plots, bar plots, and heatmaps. The tool is designed to help researchers analyze and visualize gene presence and prevalence across different geographic locations. It requires ncbi_clean.csv from FetchM and summary files in .tab (preferred) or .csv format from Abricate.

Key Features:

• Merges and processes NCBI and Abricate data.
• Analyzes gene presence across samples.
• Generates visualizations for resistance gene distributions/prevalence.

Installation

Using pip

pip install panR

Using conda

conda create -n panr_env python=3.8
conda activate panr_env
pip install git+https://github.com/Tasnimul-Arabi-Anik/PanR.git

From GitHub (Manual Installation)

git clone https://github.com/Tasnimul-Arabi-Anik/PanR.git
cd PanR
pip install -r requirements.txt

Usage

Command-Line Arguments

panR --ncbi_dir <NCBI_DIRECTORY> --abricate-dir <ABRICATE_DIRECTORY> --output-dir <OUTPUT_DIRECTORY> --fig-format <FIGURE_FORMAT>

Arguments

Argument	Description
--ncbi-dir	Path to ncbi_clean.csv file.
--abricate-dir	Directory containing Abricate summary .tab or .csv files.
--output-dir	Directory to store merged results and visualizations.
--format	Output format for figures (png, pdf, tiff,svg).

Example Run

panR --ncbi-dir ./data/ncbi_clean.csv --abricate-dir ./data/abricate --output-dir ./output --format png

Outputs

• Processed Data: Saved in output/ directory as .csv.
• Visualizations:
  • Heatmap of resistance genes across samples.
  • Bar plot showing gene presence.
  • lolipoplot showing gene counts

License

This tool is provided under the MIT License.

Author

Tasnimul Arabi Anik