VIRMOTIF: a user-friendly tool for viral sequence analysis

Pedram Rajaei, Khadijeh Hoda Jahanian, Amin Beheshti*, Shahab S. Band, Abdollah Dehzangi, Hamid Alinejad-Rokny*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Bioinformatics and computational biology have significantly contributed to the generation of vast and important knowledge that can lead to great improvements and advancements in biology and its related fields. Over the past three decades, a wide range of tools and methods have been developed and proposed to enhance performance, diagnosis, and throughput while maintaining feasibility and convenience for users. Here, we propose a new user-friendly comprehensive tool called VIRMOTIF to analyze DNA sequences. VIRMOTIF brings different tools together as one package so that users can perform their analysis as a whole and in one place. VIRMOTIF is able to complete different tasks, including computing the number or probability of motifs appearing in DNA sequences, visualizing data using the matplotlib and heatmap libraries, and clustering data using four different methods, namely K-means, PCA, Mean Shift, and ClusterMap. VIRMOTIF is the only tool with the ability to analyze genomic motifs based on their frequency and representation (D-ratio) in a virus genome.

Original languageEnglish
Article number186
Pages (from-to)1-9
Number of pages9
JournalGenes
Volume12
Issue number2
Early online date27 Jan 2021
DOIs
Publication statusPublished - Feb 2021

Bibliographical note

Copyright the Author(s) 2021. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • Sequence analysis
  • Motif analysis
  • D-ratio
  • Virus genome
  • Sequence variation

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