학술논문
GXP: Analyze and Plot Plant Omics Data in Web Browsers.
Document Type
Academic Journal
Author
Eiteneuer C; IBG-2 Plant Sciences, Forschungszentrum Jülich, 52428 Jülich, Germany.; Velasco D; Faculty of Natural Sciences, Norges Teknisk-Naturvitenskapelige Universitet, 7034 Trondheim, Norway.; Atemia J; IBG-4 Bioinformatics, Forschungszentrum Jülich, 52428 Jülich, Germany.; Wang D; IBG-2 Plant Sciences, Forschungszentrum Jülich, 52428 Jülich, Germany.; Schwacke R; IBG-4 Bioinformatics, Forschungszentrum Jülich, 52428 Jülich, Germany.; Wahl V; Max Planck Institute for Molecular Plant Physiology, 14476 Potsdam, Germany.; Schrader A; Institute for Biology I, RWTH Aachen University, 52062 Aachen, Germany.; Reimer JJ; Institute for Biology I, RWTH Aachen University, 52062 Aachen, Germany.; Faculty of Technology, University of Applied Science Emden/Leer, Molecular Biosciences, 26723 Emden, Germany.; Fahrner S; IBG-2 Plant Sciences, Forschungszentrum Jülich, 52428 Jülich, Germany.; Pieruschka R; IBG-2 Plant Sciences, Forschungszentrum Jülich, 52428 Jülich, Germany.; Schurr U; IBG-2 Plant Sciences, Forschungszentrum Jülich, 52428 Jülich, Germany.; Usadel B; IBG-4 Bioinformatics, Forschungszentrum Jülich, 52428 Jülich, Germany.; Hallab A; IBG-4 Bioinformatics, Forschungszentrum Jülich, 52428 Jülich, Germany.
Source
Publisher: MDPI AG Country of Publication: Switzerland NLM ID: 101596181 Publication Model: Electronic Cited Medium: Print ISSN: 2223-7747 (Print) Linking ISSN: 22237747 NLM ISO Abbreviation: Plants (Basel) Subsets: PubMed not MEDLINE
Subject
Language
English
ISSN
2223-7747
Abstract
Next-generation sequencing and metabolomics have become very cost and work efficient and are integrated into an ever-growing number of life science research projects. Typically, established software pipelines analyze raw data and produce quantitative data informing about gene expression or concentrations of metabolites. These results need to be visualized and further analyzed in order to support scientific hypothesis building and identification of underlying biological patterns. Some of these tools already exist, but require installation or manual programming. We developed "Gene Expression Plotter" (GXP), an RNAseq and Metabolomics data visualization and analysis tool entirely running in the user's web browser, thus not needing any custom installation, manual programming or uploading of confidential data to third party servers. Consequently, upon receiving the bioinformatic raw data analysis of RNAseq or other omics results, GXP immediately enables the user to interact with the data according to biological questions by performing knowledge-driven, in-depth data analyses and candidate identification via visualization and data exploration. Thereby, GXP can support and accelerate complex interdisciplinary omics projects and downstream analyses. GXP offers an easy way to publish data, plots, and analysis results either as a simple exported file or as a custom website. GXP is freely available on GitHub (see introduction).