Qiongyi Zhao, Woo Jun Shim, Yuliangzi Sun, Enakshi Sinniah, Sophie Shen, Mikael Boden, Nathan J Palpant
{"title":"TRIAGE: an R package for regulatory gene analysis.","authors":"Qiongyi Zhao, Woo Jun Shim, Yuliangzi Sun, Enakshi Sinniah, Sophie Shen, Mikael Boden, Nathan J Palpant","doi":"10.1093/bib/bbaf004","DOIUrl":null,"url":null,"abstract":"<p><p>Regulatory genes are critical determinants of cellular responses in development and disease, but standard RNA sequencing (RNA-seq) analysis workflows, such as differential expression analysis, have significant limitations in revealing the regulatory basis of cell identity and function. To address this challenge, we present the TRIAGE R package, a toolkit specifically designed to analyze regulatory elements in both bulk and single-cell RNA-seq datasets. The package is built upon TRIAGE methods, which leverage consortium-level H3K27me3 data to enrich for cell-type-specific regulatory regions. It facilitates the construction of efficient and adaptable pipelines for transcriptomic data analysis and visualization, with a focus on revealing regulatory gene networks. We demonstrate the utility of the TRIAGE R package using three independent transcriptomic datasets, showcasing its integration into standard analysis workflows for examining regulatory mechanisms across diverse biological contexts. The TRIAGE R package is available on GitHub at https://github.com/palpant-comp/TRIAGE_R_Package.</p>","PeriodicalId":9209,"journal":{"name":"Briefings in bioinformatics","volume":"26 1","pages":""},"PeriodicalIF":6.8000,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11725390/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Briefings in bioinformatics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/bib/bbaf004","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Regulatory genes are critical determinants of cellular responses in development and disease, but standard RNA sequencing (RNA-seq) analysis workflows, such as differential expression analysis, have significant limitations in revealing the regulatory basis of cell identity and function. To address this challenge, we present the TRIAGE R package, a toolkit specifically designed to analyze regulatory elements in both bulk and single-cell RNA-seq datasets. The package is built upon TRIAGE methods, which leverage consortium-level H3K27me3 data to enrich for cell-type-specific regulatory regions. It facilitates the construction of efficient and adaptable pipelines for transcriptomic data analysis and visualization, with a focus on revealing regulatory gene networks. We demonstrate the utility of the TRIAGE R package using three independent transcriptomic datasets, showcasing its integration into standard analysis workflows for examining regulatory mechanisms across diverse biological contexts. The TRIAGE R package is available on GitHub at https://github.com/palpant-comp/TRIAGE_R_Package.
期刊介绍:
Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data.
The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.