Abstract
BACKGROUND: Dot-plots, along with linear comparisons, are fundamental visualization methods in genome comparisons, widely used for analyzing structural variations, repeat regions, and sequence similarities. However, existing tools often have limitations in visualization flexibility, particularly requiring the concatenation of multiple sequences into a single continuous axis. This constraint can make it difficult to apply highlights or user-defined grid lines effectively, reducing interpretability in comparative genomic analyses. RESULTS: We developed blastn2dotplots, a Python 3-based tool that utilizes the Matplotlib library to generate customizable dot-plots from local blastn results. Unlike traditional approaches, blastn2dotplots treats each alignment as a separate subplot, allowing for independent axis labeling, adjustable spacing between plots, and enhanced visualization flexibility. Users can highlight specific regions of interest, apply custom grid lines, and tailor the display to suit different genomic analyses. This tool is particularly useful for chromosomal structure analyses, detection of horizontal gene transfer events, and visualization of repetitive elements, offering an intuitive and adaptable framework for sequence comparison. CONCLUSIONS: By addressing key limitations of existing dot-plot visualization tools, blastn2dotplots enhances the clarity and flexibility of comparative genomic analyses. Its ability to handle multiple alignments separately while preserving independent axis control and customization options makes it a valuable resource for a wide range of genomic studies. This tool provides a novel and effective solution for researchers needing precise and adaptable visualization of sequence alignments, thereby maximizing the potential of dot-plots in bioinformatics.