Visualization of mutations and modifications on nucleotide and protein sequences provides insights into sequence hotspots conveying biologically relevant findings derived through genomics/proteomics platforms. Lollipop plots are suitable for such visualization, where structural modules can also be easily defined to further refine meaningful information in mutation/modification patterns. Although multiple tools are available for this purpose, they are limited by the data category that can be input and lack automation. We developed a multi-purpose, opensource, completely automated web-based tool that can visualize all possible omics data inputs feasible for generating ready-to-use lollipop plots. M2Viz is a web-based application designed for visualizing modifications and mutations (M2) identified from genomics/proteomics datasets on gene and protein sequences. It is a one-stop-solution for creating lollipop plots representing DNA methylation, Single Nucleotide Variations (SNVs), protein Post-Translational Modifications (PTMs), and Single Amino Acid Variations (SAAVs). Additionally, tool can be accessed to represent profiling and differential expression/regulation datasets, with options for visualizing numerical data. The tool provides end-to-end solution for uploading, processing, annotating and graphical representation. The system integrates a Python-Django backend for data handling, an R-based engine for advanced plotting, and a React.js frontend for a responsive and interactive user experience. Nucleotide or amino acid sequences and protein domain information are retrieved from Ensembl or UniProt through REST API, removing dependency on manual data downloading. M2Viz is instrumental in visualizing DNA methylation, mutational hotspots and PTMs on gene/protein sequences. It is a valuable tool across omics pipelines and bioinformatics. The visualization pipeline is automated to reduce the need for hosting sequence and structural information in the backend, along with custom plotting flexibility. M2Viz is freely accessible at “https://ciods.in/m2viz”.
Rafi et al. (2026) studied this question.