Gene Expression Analysis Platform (GEAP) : a highly customizable, fast, versatile and ready-to-use microarray analysis platform
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/279837 |
Resumo: | There are still numerous challenges to be overcome in microarray data analysis because advanced, state-of-the-art analyses are restricted to programming users. Here we present the Gene Expression Analysis Platform, a versatile, customizable, optimized, and portable software developed for microarray analysis. GEAP was developed in C# for the graphical user interface, data querying, storage, results filtering and dynamic plotting, and R for data processing, quality analysis, and differential expression. Through a new automated system that identifies microarray file formats, retrieves contents, detects file corruption, and solves dependencies, GEAP deals with datasets independently of platform. GEAP covers 32 statistical options, supports quality assessment, differential expression from single and dual-channel experiments, and gene ontology. Users can explore results by different plots and filtering options. Finally, the entire data can be saved and organized through storage features, optimized for memory and data retrieval, with faster performance than R. These features, along with other new options, are not yet present in any microarray analysis software. GEAP accomplishes data analysis in a faster, straightforward, and friendlier way than other similar software, while keeping the flexibility for sophisticated procedures. By developing optimizations, unique customizations and new features, GEAP is destined for both advanced and non-programming users. |
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Nunes, Itamar José GuimarãesRecamonde-Mendoza, MarianaFeltes, Bruno César2024-10-10T06:48:51Z20221415-4757http://hdl.handle.net/10183/279837001147579There are still numerous challenges to be overcome in microarray data analysis because advanced, state-of-the-art analyses are restricted to programming users. Here we present the Gene Expression Analysis Platform, a versatile, customizable, optimized, and portable software developed for microarray analysis. GEAP was developed in C# for the graphical user interface, data querying, storage, results filtering and dynamic plotting, and R for data processing, quality analysis, and differential expression. Through a new automated system that identifies microarray file formats, retrieves contents, detects file corruption, and solves dependencies, GEAP deals with datasets independently of platform. GEAP covers 32 statistical options, supports quality assessment, differential expression from single and dual-channel experiments, and gene ontology. Users can explore results by different plots and filtering options. Finally, the entire data can be saved and organized through storage features, optimized for memory and data retrieval, with faster performance than R. These features, along with other new options, are not yet present in any microarray analysis software. GEAP accomplishes data analysis in a faster, straightforward, and friendlier way than other similar software, while keeping the flexibility for sophisticated procedures. By developing optimizations, unique customizations and new features, GEAP is destined for both advanced and non-programming users.application/pdfengGenetics and molecular biology. Vol. 45, no. 1 (2022), 15 p.SoftwareAnálise de dadosExpressão gênicaPesquisa biomédicaMicroarrayGene expressionBiomedical researchGene Expression Analysis Platform (GEAP) : a highly customizable, fast, versatile and ready-to-use microarray analysis platformEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001147579.pdf.txt001147579.pdf.txtExtracted Texttext/plain58074http://www.lume.ufrgs.br/bitstream/10183/279837/2/001147579.pdf.txtec122dac3755435e28f01dbdafb1fc74MD52ORIGINAL001147579.pdfTexto completo (inglês)application/pdf2532256http://www.lume.ufrgs.br/bitstream/10183/279837/1/001147579.pdf7aaa02d734c579d6744a2a89a7fe6b88MD5110183/2798372024-10-11 06:46:59.878735oai:www.lume.ufrgs.br:10183/279837Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2024-10-11T09:46:59Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Gene Expression Analysis Platform (GEAP) : a highly customizable, fast, versatile and ready-to-use microarray analysis platform |
title |
Gene Expression Analysis Platform (GEAP) : a highly customizable, fast, versatile and ready-to-use microarray analysis platform |
spellingShingle |
Gene Expression Analysis Platform (GEAP) : a highly customizable, fast, versatile and ready-to-use microarray analysis platform Nunes, Itamar José Guimarães Software Análise de dados Expressão gênica Pesquisa biomédica Microarray Gene expression Biomedical research |
title_short |
Gene Expression Analysis Platform (GEAP) : a highly customizable, fast, versatile and ready-to-use microarray analysis platform |
title_full |
Gene Expression Analysis Platform (GEAP) : a highly customizable, fast, versatile and ready-to-use microarray analysis platform |
title_fullStr |
Gene Expression Analysis Platform (GEAP) : a highly customizable, fast, versatile and ready-to-use microarray analysis platform |
title_full_unstemmed |
Gene Expression Analysis Platform (GEAP) : a highly customizable, fast, versatile and ready-to-use microarray analysis platform |
title_sort |
Gene Expression Analysis Platform (GEAP) : a highly customizable, fast, versatile and ready-to-use microarray analysis platform |
author |
Nunes, Itamar José Guimarães |
author_facet |
Nunes, Itamar José Guimarães Recamonde-Mendoza, Mariana Feltes, Bruno César |
author_role |
author |
author2 |
Recamonde-Mendoza, Mariana Feltes, Bruno César |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Nunes, Itamar José Guimarães Recamonde-Mendoza, Mariana Feltes, Bruno César |
dc.subject.por.fl_str_mv |
Software Análise de dados Expressão gênica Pesquisa biomédica |
topic |
Software Análise de dados Expressão gênica Pesquisa biomédica Microarray Gene expression Biomedical research |
dc.subject.eng.fl_str_mv |
Microarray Gene expression Biomedical research |
description |
There are still numerous challenges to be overcome in microarray data analysis because advanced, state-of-the-art analyses are restricted to programming users. Here we present the Gene Expression Analysis Platform, a versatile, customizable, optimized, and portable software developed for microarray analysis. GEAP was developed in C# for the graphical user interface, data querying, storage, results filtering and dynamic plotting, and R for data processing, quality analysis, and differential expression. Through a new automated system that identifies microarray file formats, retrieves contents, detects file corruption, and solves dependencies, GEAP deals with datasets independently of platform. GEAP covers 32 statistical options, supports quality assessment, differential expression from single and dual-channel experiments, and gene ontology. Users can explore results by different plots and filtering options. Finally, the entire data can be saved and organized through storage features, optimized for memory and data retrieval, with faster performance than R. These features, along with other new options, are not yet present in any microarray analysis software. GEAP accomplishes data analysis in a faster, straightforward, and friendlier way than other similar software, while keeping the flexibility for sophisticated procedures. By developing optimizations, unique customizations and new features, GEAP is destined for both advanced and non-programming users. |
publishDate |
2022 |
dc.date.issued.fl_str_mv |
2022 |
dc.date.accessioned.fl_str_mv |
2024-10-10T06:48:51Z |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
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publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10183/279837 |
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1415-4757 |
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001147579 |
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http://hdl.handle.net/10183/279837 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Genetics and molecular biology. Vol. 45, no. 1 (2022), 15 p. |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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