| Journal: | Genetics and molecular biology |
| Database: | PERIÓDICA |
| System number: | 000459238 |
| ISSN: | 1415-4757 |
| Authors: | Nunes, Itamar José Guimarães1 Recamonde Mendoza, Mariana1 Feltes, Bruno César1 |
| Institutions: | 1Universidade Federal do Rio Grande do Sul, Instituto de Informatica, Porto Alegre, Rio Grande do Sul. Brasil |
| Year: | 2022 |
| Volumen: | 45 |
| Number: | 1 |
| Country: | Brasil |
| Language: | Inglés |
| Document type: | Artículo |
| Approach: | Experimental, aplicado |
| English abstract | 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 |
| Disciplines: | Biología |
| Keyword: | Genética, Microarreglos genéticos, Expresión génica, GEAP |
| Keyword: | Genetics, Microarrays, Gene expression, GEAP |
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