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ivTerm—An R package for interactive visualization of functional analysis results of meta‐omics data
Author(s) -
Dong Xiaorui,
Xue Hongzhang,
Wei Chaochun
Publication year - 2021
Publication title -
journal of cellular biochemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.028
H-Index - 165
eISSN - 1097-4644
pISSN - 0730-2312
DOI - 10.1002/jcb.30019
Subject(s) - computer science , visualization , metadata , data visualization , download , metagenomics , graphical user interface , interactive visualization , data science , information retrieval , data mining , world wide web , biology , biochemistry , gene , programming language
Interpreting functional analysis results derived from environmental samples using direct sequencing meta-omics data, including metagenomics and meta-transcriptomics data, is challenging due to their complexity. Visualization of functional analysis results can help researchers discover relevant biological insights. Despite the availability of many R packages, there lacks interactive and comprehensive graphic systems for displaying functional terms and corresponding genes in meta-omics analysis results. Here, we present ivTerm, an R-shiny package with a user-friendly graphical interface that enables users to inspect functional annotations, compare results across multiple experiments, create customized charts, and download these charts. It provides various basic and innovative chart types to visualize functional terms and involved genes. Users can also browse the description of terms obtained from the database web servers automatically. Two examples, including a metagenome analysis data for human gut and a meta-transcriptome data for coral symbiomes, are given to show the usage of ivTerm. In the end, we compared ivTerm with existing tools with similar functions, such as GOplot, ViSEAGO, and Chordomics. The tool ivTerm is convenient and efficient for biologists to gain an integrated view and develop deep insights by interactive analysis of meta-omics data. It can accelerate the procedure to develop insights from complex meta-omics data. The code for ivTerm is freely available at https://github.com/SJTU-CGM/ivTerm.