Whole Exome Sequencing (WES) is a genomic technique that sequences only the protein-coding regions (exons) of the genome. In this article, we introduce a new Python package that allows the easy visualization of WES data.
Introduction
wes_data_analysis package provides a comprehensive set of Python scripts for visualizing whole exome sequencing (WES) data. It allows to generate insightful charts and plots, including:
- scatter plot
- bubble plot
- copy number variation (CNV) heatmap
- CNV amplification data
- correlation heatmap
- arm level correlation
- CNV G-score plot
- Gistic plot
- Manhattan plot
- oncoplot
The package consists of individual Python scripts for each plot. The plots and charts were generated using sample data and/or randomly generated data in CSV file formats. You will find the sample data files along with the package.
Availability
The package can be downloaded from GitHub. There, you will find the scripts (ipynb) that you can run in jupyter-notebook or any other software such as VS Code along with the sample data files.
Usage
Download the package and unzip all files. There, you will find a directory named ‘sample_data’, where all sample data files are located and all the Python scripts (in .ipynb format). Run the scripts using Jupyter Notebook or any other software such as VS Code. Ensure to provide full path of your input data or simply paste the input file in the same directory (update the input file path if needed).
Discussion
This package provides easy visualization of WES data from CSV inout files. It generates various kinds of plots and charts that help in better visualization and allows users to customize the scripts as per their needs. This version reads files in CSV/TSV files. In future, this packge will support other file formats such as VCF, BAM, etc.
How to Cite?
Faiza, M., 2025. wes_data_analysis: Whole Exome Sequencing (WES) Data visualization Toolkit., 11(3): page 4-8. https://bioinformaticsreview.com/20250325/wes_data_analysis-whole-exome-sequencing-wes-data-visualization-toolkit.