iGEAK: an interactive gene expression analysis kit for seamless workflow using the R/shiny platform

The use of microarrays and RNA-seq technologies is ubiquitous for transcriptome analyses in modern biology. With proper analysis tools, the differential gene expression analysis process can be significantly accelerated. Many open-source programs provide cutting-edge techniques, but these often requi...

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Veröffentlicht in:BMC genomics 2019-03, Vol.20 (1), p.177-7, Article 177
Hauptverfasser: Choi, Kwangmin, Ratner, Nancy
Format: Artikel
Sprache:eng
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Zusammenfassung:The use of microarrays and RNA-seq technologies is ubiquitous for transcriptome analyses in modern biology. With proper analysis tools, the differential gene expression analysis process can be significantly accelerated. Many open-source programs provide cutting-edge techniques, but these often require programming skills and lack intuitive and interactive or graphical user interfaces. To avoid bottlenecks impeding seamless analysis processing, we have developed an Interactive Gene Expression Analysis Kit, we term iGEAK, focusing on usability and interactivity. iGEAK is designed to be a simple, intuitive, light-weight that contrasts with heavy-duty programs. iGEAK is an R/Shiny-based client-side desktop application, providing an interactive gene expression data analysis pipeline for microarray and RNA-seq data. Gene expression data can be intuitively explored using a seamless analysis pipeline consisting of sample selection, differentially expressed gene prediction, protein-protein interaction, and gene set enrichment analyses. For each analysis step, users can easily alter parameters to mine more relevant biological information. iGEAK is the outcome of close collaboration with wet-bench biologists who are eager to easily explore, mine, and analyze new or public microarray and RNA-seq data. We designed iGEAK as a gene expression analysis pipeline tool to provide essential analysis steps and a user-friendly interactive graphical user interface. iGEAK enables users without programing knowledge to comfortably perform differential gene expression predictions and downstream analyses. iGEAK packages, manuals, tutorials, sample datasets are available at the iGEAK project homepage ( https://sites.google.com/view/iGEAK ).
ISSN:1471-2164
1471-2164
DOI:10.1186/s12864-019-5548-x