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

Chirag ParsaniaRuiwen ChenPooja SethiyaZhengqiang MiaoLiguo DongKoon Ho Wong
Published in: Briefings in bioinformatics (2023)
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).
Keyphrases
  • data analysis
  • rna seq
  • single cell
  • high throughput
  • gene expression
  • bioinformatics analysis
  • dna methylation
  • healthcare
  • endothelial cells
  • mental health
  • deep learning
  • small molecule
  • multidrug resistant