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Genealyzer: web application for the analysis and comparison of gene expression data

BACKGROUND: Gene expression profiling is a widely adopted method in areas like drug development or functional gene analysis. Microarray data of gene expression experiments is still commonly used and widely available for retrospective analyses. However, due to to changes of the underlying technologie...

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Autores principales: Lietz, Kristina, Saremi, Babak, Wiese, Lena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10111666/
https://www.ncbi.nlm.nih.gov/pubmed/37069540
http://dx.doi.org/10.1186/s12859-023-05266-4
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author Lietz, Kristina
Saremi, Babak
Wiese, Lena
author_facet Lietz, Kristina
Saremi, Babak
Wiese, Lena
author_sort Lietz, Kristina
collection PubMed
description BACKGROUND: Gene expression profiling is a widely adopted method in areas like drug development or functional gene analysis. Microarray data of gene expression experiments is still commonly used and widely available for retrospective analyses. However, due to to changes of the underlying technologies data sets from different technologies are often difficult to compare and thus a multitude of already available data becomes difficult to use. We present a web application that abstracts away mathematical and programmatical details in order to enable a convenient and customizable analysis of microarray data for large-scale reproducibility studies. In addition, the web application provides a feature that allows easy access to large microarray repositories. RESULTS: Our web application consists of three basic steps which are necessary for a differential gene expression analysis as well as Gene Ontology (GO) enrichment analysis and the comparison of multiple analysis results. Genealyzer can handle Affymetrix data as well as one-channel and two-channel Agilent data. All steps are visualized with meaningful plots. The application offers flexible analysis while being intuitively operable. CONCLUSIONS: Our web application provides a unified platform for analysing microarray data, while allowing users to compare the results of different technologies and organisms. Beyond reproducibility, this also offers many possibilities for gaining further insights from existing study data, especially since data from different technologies or organisms can also be compared. The web application can be accessed via this URL: https://genealyzer.item.fraunhofer.de/. Login credentials can be found at the end.
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spelling pubmed-101116662023-04-19 Genealyzer: web application for the analysis and comparison of gene expression data Lietz, Kristina Saremi, Babak Wiese, Lena BMC Bioinformatics Software BACKGROUND: Gene expression profiling is a widely adopted method in areas like drug development or functional gene analysis. Microarray data of gene expression experiments is still commonly used and widely available for retrospective analyses. However, due to to changes of the underlying technologies data sets from different technologies are often difficult to compare and thus a multitude of already available data becomes difficult to use. We present a web application that abstracts away mathematical and programmatical details in order to enable a convenient and customizable analysis of microarray data for large-scale reproducibility studies. In addition, the web application provides a feature that allows easy access to large microarray repositories. RESULTS: Our web application consists of three basic steps which are necessary for a differential gene expression analysis as well as Gene Ontology (GO) enrichment analysis and the comparison of multiple analysis results. Genealyzer can handle Affymetrix data as well as one-channel and two-channel Agilent data. All steps are visualized with meaningful plots. The application offers flexible analysis while being intuitively operable. CONCLUSIONS: Our web application provides a unified platform for analysing microarray data, while allowing users to compare the results of different technologies and organisms. Beyond reproducibility, this also offers many possibilities for gaining further insights from existing study data, especially since data from different technologies or organisms can also be compared. The web application can be accessed via this URL: https://genealyzer.item.fraunhofer.de/. Login credentials can be found at the end. BioMed Central 2023-04-17 /pmc/articles/PMC10111666/ /pubmed/37069540 http://dx.doi.org/10.1186/s12859-023-05266-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Software
Lietz, Kristina
Saremi, Babak
Wiese, Lena
Genealyzer: web application for the analysis and comparison of gene expression data
title Genealyzer: web application for the analysis and comparison of gene expression data
title_full Genealyzer: web application for the analysis and comparison of gene expression data
title_fullStr Genealyzer: web application for the analysis and comparison of gene expression data
title_full_unstemmed Genealyzer: web application for the analysis and comparison of gene expression data
title_short Genealyzer: web application for the analysis and comparison of gene expression data
title_sort genealyzer: web application for the analysis and comparison of gene expression data
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10111666/
https://www.ncbi.nlm.nih.gov/pubmed/37069540
http://dx.doi.org/10.1186/s12859-023-05266-4
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