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FungiExpresZ: an intuitive package for fungal gene expression data analysis, visualization and discovery
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 Fu...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025439/ https://www.ncbi.nlm.nih.gov/pubmed/36806894 http://dx.doi.org/10.1093/bib/bbad051 |
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author | Parsania, Chirag Chen, Ruiwen Sethiya, Pooja Miao, Zhengqiang Dong, Liguo Wong, Koon Ho |
author_facet | Parsania, Chirag Chen, Ruiwen Sethiya, Pooja Miao, Zhengqiang Dong, Liguo Wong, Koon Ho |
author_sort | Parsania, Chirag |
collection | PubMed |
description | 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). |
format | Online Article Text |
id | pubmed-10025439 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-100254392023-03-21 FungiExpresZ: an intuitive package for fungal gene expression data analysis, visualization and discovery Parsania, Chirag Chen, Ruiwen Sethiya, Pooja Miao, Zhengqiang Dong, Liguo Wong, Koon Ho Brief Bioinform Problem Solving Protocol 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). Oxford University Press 2023-02-17 /pmc/articles/PMC10025439/ /pubmed/36806894 http://dx.doi.org/10.1093/bib/bbad051 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Problem Solving Protocol Parsania, Chirag Chen, Ruiwen Sethiya, Pooja Miao, Zhengqiang Dong, Liguo Wong, Koon Ho FungiExpresZ: an intuitive package for fungal gene expression data analysis, visualization and discovery |
title | FungiExpresZ: an intuitive package for fungal gene expression data analysis, visualization and discovery |
title_full | FungiExpresZ: an intuitive package for fungal gene expression data analysis, visualization and discovery |
title_fullStr | FungiExpresZ: an intuitive package for fungal gene expression data analysis, visualization and discovery |
title_full_unstemmed | FungiExpresZ: an intuitive package for fungal gene expression data analysis, visualization and discovery |
title_short | FungiExpresZ: an intuitive package for fungal gene expression data analysis, visualization and discovery |
title_sort | fungiexpresz: an intuitive package for fungal gene expression data analysis, visualization and discovery |
topic | Problem Solving Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025439/ https://www.ncbi.nlm.nih.gov/pubmed/36806894 http://dx.doi.org/10.1093/bib/bbad051 |
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