VisFeature: a stand-alone program for visualizing and analyzing statistical features of biological sequences

Author:

Wang Jun1ORCID,Du Pu-Feng1,Xue Xin-Yu1,Li Guang-Ping1,Zhou Yuan-Ke1,Zhao Wei1,Lin Hao2,Chen Wei34

Affiliation:

1. College of Intelligence and Computing, Tianjin University, Tianjin 300350, China

2. Key Laboratory for Neuro-Information of Ministry of Education, School of Life Science and Technology, Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054, China

3. Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China

4. Center for Genomics and Computational Biology, School of Life Sciences, North China University of Science and Technology, Tangshan 063000, China

Abstract

Abstract Summary Many efforts have been made in developing bioinformatics algorithms to predict functional attributes of genes and proteins from their primary sequences. One challenge in this process is to intuitively analyze and to understand the statistical features that have been selected by heuristic or iterative methods. In this paper, we developed VisFeature, which aims to be a helpful software tool that allows the users to intuitively visualize and analyze statistical features of all types of biological sequence, including DNA, RNA and proteins. VisFeature also integrates sequence data retrieval, multiple sequence alignments and statistical feature generation functions. Availability and implementation VisFeature is a desktop application that is implemented using JavaScript/Electron and R. The source codes of VisFeature are freely accessible from the GitHub repository (https://github.com/wangjun1996/VisFeature). The binary release, which includes an example dataset, can be freely downloaded from the same GitHub repository (https://github.com/wangjun1996/VisFeature/releases). Contact pdu@tju.edu.cn or chenweiimu@gmail.com Supplementary information Supplementary data are available at Bioinformatics online.

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Natural Science Foundation for Distinguished Young Scholar of Hebei Province

Open Project Funding of CAS Key Lab of Network Data Science and Technology, Institute of Computing Technology, Chinese Academy of Sciences

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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