SimPlot++: a Python application for representing sequence similarity and detecting recombination.

Area of Science:

• Bioinformatics
• Evolutionary Biology
• Computational Biology

Background:

• Accurate detection of sequence similarity is crucial for evolutionary analyses.
• Identifying homologous recombination events is essential for understanding evolutionary processes.

Purpose of the Study:

• To develop an open-source, multiplatform application for sequence similarity analysis and recombination detection.
• To provide researchers with a tool for generating publication-quality plots and analyzing sequence similarity networks.

Main Methods:

• Developed SimPlot++ using Python, incorporating 63 nucleotide and 20 amino acid distance models.
• Implemented various statistical tests (Φ, Max-χ2, NSS, proportion tests) for intergenic and intragenic recombination detection.
• Enabled the generation and analysis of interactive sequence similarity networks with multicore processing support.

Main Results:

• SimPlot++ produces high-quality sequence similarity plots and detects recombination events effectively.
• The application supports a wide range of distance models and statistical tests.
• Interactive sequence similarity networks can be generated and analyzed.

Conclusions:

• SimPlot++ is a versatile and powerful tool for evolutionary sequence analysis.
• Its open-source, multiplatform nature makes it accessible to a broad research community.
• The application facilitates accurate detection of sequence similarity and recombination, aiding evolutionary studies.