VIRMOTIF: A User-Friendly Tool for Viral Sequence Analysis

被引:13
|
作者
Rajaei, Pedram [1 ]
Jahanian, Khadijeh Hoda [2 ]
Beheshti, Amin [3 ]
Band, Shahab S. [4 ]
Dehzangi, Abdollah [5 ,6 ]
Alinejad-Rokny, Hamid [2 ,7 ]
机构
[1] Amirkabir Univ Technol, Tehran 346512, Iran
[2] Macquarie Univ, Hlth Data Analyt Program, AI Enabled Proc AIP Res Ctr, Sydney, NSW 2109, Australia
[3] Macquarie Univ, Dept Comp, Sydney, NSW 2109, Australia
[4] Natl Yunlin Univ Sci & Technol, Coll Future, Future Technol Res Ctr, 123 Univ Rd, Touliu 64002, Yunlin, Taiwan
[5] Rutgers State Univ, Dept Comp Sci, Camden, NJ 08102 USA
[6] Rutgers State Univ, Ctr Computat & Integrat Biol, Camden, NJ 08102 USA
[7] Univ New South Wales, Grad Sch Biomed Engn, Biol & Med Machine Learning Lab BML, Sydney, NSW 2052, Australia
关键词
sequence analysis; motif analysis; D-ratio; virus genome; sequence variation;
D O I
10.3390/genes12020186
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
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.
引用
收藏
页数:9
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