This title appears in the Scientific Report :
2022
Please use the identifier:
http://dx.doi.org/10.3390/plants11060745 in citations.
Please use the identifier: http://hdl.handle.net/2128/31000 in citations.
GXP: Analyze and Plot Plant Omics Data in Web Browsers
GXP: Analyze and Plot Plant Omics Data in Web Browsers
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 concentra...
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Personal Name(s): | Eiteneuer, Constantin |
---|---|
Velasco, David / Atemia, Joseph / Wang, Dan / Schwacke, Rainer / Wahl, Vanessa / Schrader, Andrea / Reimer, Julia J. / Fahrner, Sven / Pieruschka, Roland / Schurr, Ulrich / Usadel, Björn / Hallab, Asis (Corresponding author) | |
Contributing Institute: |
Pflanzenwissenschaften; IBG-2 Bioinformatik; IBG-4 |
Published in: | Plants, 11 (2022) 6, S. 745 - |
Imprint: |
Basel
MDPI
2022
|
DOI: |
10.3390/plants11060745 |
PubMed ID: |
35336631 |
Document Type: |
Journal Article |
Research Program: |
Biological and environmental resources for sustainable use |
Link: |
OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://hdl.handle.net/2128/31000 in citations.
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). |