4.7 Article

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

Journal

BRIEFINGS IN BIOINFORMATICS
Volume 24, Issue 2, Pages -

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bib/bbad051

Keywords

FungiExpresZ; bioinformatics tool; RNA-seq database; data visualization; data analysis; fungi

Ask authors/readers for more resources

This study presents an intuitive user-friendly platform called FungiExpresZ for gene expression data analysis and visualization, aiming to help wet-lab scientists without computer programming skills to become independent in bioinformatics analysis. The platform includes commonly used data analysis tools and pre-processed RNA-seq datasets of various fungal species, including human, plant, and insect pathogens. FungiExpresZ enables users to analyze their own data alone or in combination with public RNA-seq data for integrated analysis, overcoming limitations in genomics data analysis.
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 () and an offline R-Shiny package ().

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available