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Technical Note

GXP: Analyze and Plot Plant Omics Data in Web Browsers

1
IBG-2 Plant Sciences, Forschungszentrum Jülich, 52428 Jülich, Germany
2
Faculty of Natural Sciences, Norges Teknisk-Naturvitenskapelige Universitet, 7034 Trondheim, Norway
3
IBG-4 Bioinformatics, Forschungszentrum Jülich, 52428 Jülich, Germany
4
Max Planck Institute for Molecular Plant Physiology, 14476 Potsdam, Germany
5
Institute for Biology I, RWTH Aachen University, 52062 Aachen, Germany
6
Faculty of Technology, University of Applied Science Emden/Leer, Molecular Biosciences, 26723 Emden, Germany
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editors: Ji Huang and Yufeng Wu
Plants 2022, 11(6), 745; https://doi.org/10.3390/plants11060745
Received: 11 January 2022 / Revised: 15 February 2022 / Accepted: 1 March 2022 / Published: 11 March 2022
(This article belongs to the Special Issue Plant Bioinformatics: Applications and Databases)
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) View Full-Text
Keywords: RNA sequencing; metabolomics; data visualization; overrepresentation analysis; correlation; cluster analysis; principal component analysis; scientific plotting; Mapman; Mercator RNA sequencing; metabolomics; data visualization; overrepresentation analysis; correlation; cluster analysis; principal component analysis; scientific plotting; Mapman; Mercator
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MDPI and ACS Style

Eiteneuer, C.; Velasco, D.; Atemia, J.; Wang, D.; Schwacke, R.; Wahl, V.; Schrader, A.; Reimer, J.J.; Fahrner, S.; Pieruschka, R.; Schurr, U.; Usadel, B.; Hallab, A. GXP: Analyze and Plot Plant Omics Data in Web Browsers. Plants 2022, 11, 745. https://doi.org/10.3390/plants11060745

AMA Style

Eiteneuer C, Velasco D, Atemia J, Wang D, Schwacke R, Wahl V, Schrader A, Reimer JJ, Fahrner S, Pieruschka R, Schurr U, Usadel B, Hallab A. GXP: Analyze and Plot Plant Omics Data in Web Browsers. Plants. 2022; 11(6):745. https://doi.org/10.3390/plants11060745

Chicago/Turabian Style

Eiteneuer, Constantin, David Velasco, Joseph Atemia, Dan Wang, Rainer Schwacke, Vanessa Wahl, Andrea Schrader, Julia J. Reimer, Sven Fahrner, Roland Pieruschka, Ulrich Schurr, Björn Usadel, and Asis Hallab. 2022. "GXP: Analyze and Plot Plant Omics Data in Web Browsers" Plants 11, no. 6: 745. https://doi.org/10.3390/plants11060745

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