Residential Collegefalse
Status已發表Published
FungiExpresZ: an intuitive package for fungal gene expression data analysis, visualization and discovery
Parsania, Chirag1; Chen, Ruiwen1; Sethiya, Pooja1; Miao, Zhengqiang1; Dong, Liguo1; Wong, Koon Ho1,2,3
2023-03-19
Source PublicationBriefings in Bioinformatics
ISSN1467-5463
Volume24Issue:2Pages:1–12
Abstract

Bioinformatics analysis and visualization of high-throughput gene expression data require extensive computer programming skills, posing a bottleneck for many wet-lab scientists. In this work, we present an intuitive user-friendly platform for gene expression data analysis and visualization called FungiExpresZ. FungiExpresZ aims to help wet-lab scientists with little to no knowledge of computer programming to become self-reliant in bioinformatics analysis and generating publication-ready figures. The platform contains many commonly used data analysis tools and an extensive collection of pre-processed public ribonucleic acid sequencing (RNA-seq) datasets of many fungal species, including important human, plant and insect pathogens. Users may analyse their data alone or in combination with public RNA-seq data for an integrated analysis. The FungiExpresZ platform helps wet-lab scientists to overcome their limitations in genomics data analysis and can be applied to analyse data of any organism. FungiExpresZ is available as an online web-based tool (https://cparsania.shinyapps.io/FungiExpresZ/) and an offline R-Shiny package (https://github.com/cparsania/FungiExpresZ).

KeywordFungiexpresz Bioinformatics Tool Rna-seq Database Data Visualization Data Analysis Fungi
DOI10.1093/bib/bbad051
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaBiochemistry & Molecular Biology ; Mathematical & Computational Biology
WOS SubjectBiochemical Research Methods ; Mathematical & Computational Biology
WOS IDWOS:000936333900001
Scopus ID2-s2.0-85150666597
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionMinistry of Education Frontiers Science Center for Precision Oncology, University of Macau
Faculty of Health Sciences
Institute of Translational Medicine
Corresponding AuthorWong, Koon Ho
Affiliation1.Faculty of Health Sciences, University of Macau, Macau SAR of China, China
2.Institute of Translational Medicine, University of Macau, Macau SAR of China, China
3.Ministry of Education Frontiers Science Center for Precision Oncology, University of Macau, Macau, China
First Author AffilicationFaculty of Health Sciences
Corresponding Author AffilicationFaculty of Health Sciences;  University of Macau
Recommended Citation
GB/T 7714
Parsania, Chirag,Chen, Ruiwen,Sethiya, Pooja,et al. FungiExpresZ: an intuitive package for fungal gene expression data analysis, visualization and discovery[J]. Briefings in Bioinformatics, 2023, 24(2), 1–12.
APA Parsania, Chirag., Chen, Ruiwen., Sethiya, Pooja., Miao, Zhengqiang., Dong, Liguo., & Wong, Koon Ho (2023). FungiExpresZ: an intuitive package for fungal gene expression data analysis, visualization and discovery. Briefings in Bioinformatics, 24(2), 1–12.
MLA Parsania, Chirag,et al."FungiExpresZ: an intuitive package for fungal gene expression data analysis, visualization and discovery".Briefings in Bioinformatics 24.2(2023):1–12.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Parsania, Chirag]'s Articles
[Chen, Ruiwen]'s Articles
[Sethiya, Pooja]'s Articles
Baidu academic
Similar articles in Baidu academic
[Parsania, Chirag]'s Articles
[Chen, Ruiwen]'s Articles
[Sethiya, Pooja]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Parsania, Chirag]'s Articles
[Chen, Ruiwen]'s Articles
[Sethiya, Pooja]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.