Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8952246/
https://www.ncbi.nlm.nih.gov/pubmed/35336631
http://dx.doi.org/10.3390/plants11060745
_version_ 1784675567694512128
author 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
author_facet 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
author_sort Eiteneuer, Constantin
collection PubMed
description 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)
format Online
Article
Text
id pubmed-8952246
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-89522462022-03-26 GXP: Analyze and Plot Plant Omics Data in Web Browsers 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 Plants (Basel) Technical Note 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) MDPI 2022-03-11 /pmc/articles/PMC8952246/ /pubmed/35336631 http://dx.doi.org/10.3390/plants11060745 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Technical Note
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
GXP: Analyze and Plot Plant Omics Data in Web Browsers
title GXP: Analyze and Plot Plant Omics Data in Web Browsers
title_full GXP: Analyze and Plot Plant Omics Data in Web Browsers
title_fullStr GXP: Analyze and Plot Plant Omics Data in Web Browsers
title_full_unstemmed GXP: Analyze and Plot Plant Omics Data in Web Browsers
title_short GXP: Analyze and Plot Plant Omics Data in Web Browsers
title_sort gxp: analyze and plot plant omics data in web browsers
topic Technical Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8952246/
https://www.ncbi.nlm.nih.gov/pubmed/35336631
http://dx.doi.org/10.3390/plants11060745
work_keys_str_mv AT eiteneuerconstantin gxpanalyzeandplotplantomicsdatainwebbrowsers
AT velascodavid gxpanalyzeandplotplantomicsdatainwebbrowsers
AT atemiajoseph gxpanalyzeandplotplantomicsdatainwebbrowsers
AT wangdan gxpanalyzeandplotplantomicsdatainwebbrowsers
AT schwackerainer gxpanalyzeandplotplantomicsdatainwebbrowsers
AT wahlvanessa gxpanalyzeandplotplantomicsdatainwebbrowsers
AT schraderandrea gxpanalyzeandplotplantomicsdatainwebbrowsers
AT reimerjuliaj gxpanalyzeandplotplantomicsdatainwebbrowsers
AT fahrnersven gxpanalyzeandplotplantomicsdatainwebbrowsers
AT pieruschkaroland gxpanalyzeandplotplantomicsdatainwebbrowsers
AT schurrulrich gxpanalyzeandplotplantomicsdatainwebbrowsers
AT usadelbjorn gxpanalyzeandplotplantomicsdatainwebbrowsers
AT hallabasis gxpanalyzeandplotplantomicsdatainwebbrowsers