Albert Garcia Lopez, Daniela Albrecht-Eckardt, Gianni Panagiotou, Sascha Schäuble
{"title":"FungiFun3: Systemic gene set enrichment analysis for fungal species.","authors":"Albert Garcia Lopez, Daniela Albrecht-Eckardt, Gianni Panagiotou, Sascha Schäuble","doi":"10.1093/bioinformatics/btae620","DOIUrl":null,"url":null,"abstract":"<p><strong>Summary: </strong>The ever-growing amount of genome-wide omics data paved the way for solving life science problems in a data-driven manner. Among others, enrichment analysis is part of the standard analysis arsenal to determine systemic signals in any given transcriptomic or proteomic data. Only a part of the members of the fungal kingdom, however, can be analyzed via public web applications, despite the global rise of fungal pathogens and their increasing resistance to antimycotics. We present FungiFun3, a major update of our user-friendly gene set enrichment web application dedicated to fungi. FungiFun3 was rebuilt from scratch to support a modern and easy-to-use web interface and supports more than four-fold more fungal strains (n = 1,287 in total) than its predecessor. In addition, it also allows ranked gene set enrichment analysis at the genomic scale. FungiFun3 thus serves as a starting hub for identifying molecular signals in omics data sets related to a vast amount of available fungal strains including human fungal pathogens of the WHO's priority list and far beyond.</p><p><strong>Availability and implementation: </strong>FungiFun3, including sample data and FAQ, is freely available at https://fungifun3.hki-jena.de/.</p><p><strong>Supplementary information: </strong>Supplementary data are available at Bioinformatics online.</p>","PeriodicalId":93899,"journal":{"name":"Bioinformatics (Oxford, England)","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics (Oxford, England)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioinformatics/btae620","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Summary: The ever-growing amount of genome-wide omics data paved the way for solving life science problems in a data-driven manner. Among others, enrichment analysis is part of the standard analysis arsenal to determine systemic signals in any given transcriptomic or proteomic data. Only a part of the members of the fungal kingdom, however, can be analyzed via public web applications, despite the global rise of fungal pathogens and their increasing resistance to antimycotics. We present FungiFun3, a major update of our user-friendly gene set enrichment web application dedicated to fungi. FungiFun3 was rebuilt from scratch to support a modern and easy-to-use web interface and supports more than four-fold more fungal strains (n = 1,287 in total) than its predecessor. In addition, it also allows ranked gene set enrichment analysis at the genomic scale. FungiFun3 thus serves as a starting hub for identifying molecular signals in omics data sets related to a vast amount of available fungal strains including human fungal pathogens of the WHO's priority list and far beyond.
Availability and implementation: FungiFun3, including sample data and FAQ, is freely available at https://fungifun3.hki-jena.de/.
Supplementary information: Supplementary data are available at Bioinformatics online.