FungiExpresZ: an intuitive package for fungal gene expression data analysis, visualization and discovery

Author:

Parsania Chirag1ORCID,Chen Ruiwen1ORCID,Sethiya Pooja1ORCID,Miao Zhengqiang1,Dong Liguo1ORCID,Wong Koon Ho12ORCID

Affiliation:

1. Faculty of Health Sciences, University of Macau , Macau SAR of China

2. Institute of Translational Medicine, University of Macau , Macau SAR of China

Abstract

AbstractBioinformatics 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).

Funder

Science and Technology Development Fund

University of Macau – Dr Stanley Ho Medical Development Foundation

Research Services and Knowledge Transfer Office

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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