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AlignStatPlot: An R package and online tool for robust sequence alignment statistics and innovative visualization of big data

Author

Listed:
  • Alsamman M Alsamman
  • Achraf El Allali
  • Morad M Mokhtar
  • Khaled Al-Sham’aa
  • Ahmed E Nassar
  • Khaled H Mousa
  • Zakaria Kehel

Abstract

Multiple sequence alignment (MSA) is essential for understanding genetic variations controlling phenotypic traits in all living organisms. The post-analysis of MSA results is a difficult step for researchers who do not have programming skills. Especially those working with large scale data and looking for potential variations or variable sample groups. Generating bi-allelic data and the comparison of wild and alternative gene forms are important steps in population genetics. Customising MSA visualisation for a single page view is difficult, making viewing potential indels and variations challenging. There are currently no bioinformatics tools that permit post-MSA analysis, in which data on gene and single nucleotide scales could be combined with gene annotations and used for cluster analysis. We introduce “AlignStatPlot,” a new R package and online tool that is well-documented and easy-to use for MSA and post-MSA analysis. This tool performs both traditional and cutting-edge analyses on sequencing data and generates new visualisation methods for MSA results. When compared to currently available tools, AlignStatPlot provides a robust ability to handle and visualise diversity data, while the online version will save time and encourage researchers to focus on explaining their findings. It is a simple tool that can be used in conjunction with population genetics software.

Suggested Citation

  • Alsamman M Alsamman & Achraf El Allali & Morad M Mokhtar & Khaled Al-Sham’aa & Ahmed E Nassar & Khaled H Mousa & Zakaria Kehel, 2023. "AlignStatPlot: An R package and online tool for robust sequence alignment statistics and innovative visualization of big data," PLOS ONE, Public Library of Science, vol. 18(9), pages 1-11, September.
  • Handle: RePEc:plo:pone00:0291204
    DOI: 10.1371/journal.pone.0291204
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