| Journal: | Brazilian journal of medical and biological research |
| Database: | PERIÓDICA |
| System number: | 000350321 |
| ISSN: | 0100-879X |
| Authors: | Vicentini, R1 Menossi, M2 |
| Institutions: | 1Universidade Estadual de Campinas, Centro de Biologia Molecular e Engenharia Genetica, Campinas, Sao Paulo. Brasil 2Universidade Estadual de Campinas, Instituto de Biologia, Campinas, Sao Paulo. Brasil |
| Year: | 2007 |
| Season: | May |
| Volumen: | 40 |
| Number: | 5 |
| Pages: | 615-619 |
| Country: | Brasil |
| Language: | Inglés |
| Document type: | Artículo |
| Approach: | Experimental, aplicado |
| English abstract | The pipeline for macro- and microarray analyses (PMmA) is a set of scripts with a web interface developed to analyze DNA array data generated by array image quantification software. PMmA is designed for use with single- or double-color array data and to work as a pipeline in five classes (data format, normalization, data analysis, clustering, and array maps). It can also be used as a plugin in the BioArray Software Environment, an open-source database for array analysis, or used in a local version of the web service. All scripts in PMmA were developed in the PERL programming language and statistical analysis functions were implemented in the R statistical language. Consequently, our package is a platform-independent software. Our algorithms can correctly select almost 90% of the differentially expressed genes, showing a superior performance compared to other methods of analysis. The pipeline software has been applied to 1536 expressed sequence tags macroarray public data of sugarcane exposed to cold for 3 to 48 h. PMmA identified thirty cold-responsive genes previously unidentified in this public dataset. Fourteen genes were up-regulated, two had a variable expression and the other fourteen were down-regulated in the treatments. These new findings certainly were a consequence of using a superior statistical analysis approach, since the original study did not take into account the dependence of data variability on the average signal intensity of each gene. The web interface, supplementary information, and the package source code are available, free, to non-commercial users at http://ipe.cbmeg.unicamp.br/pub/PMmA |
| Disciplines: | Medicina |
| Keyword: | Genética, Informática médica, Análisis genético, Microarreglos genéticos, Software |
| Keyword: | Medicine, Genetics, Medical informatics, Genetic analysis, Genetic microarrays, Software |
| Full text: | Texto completo (Ver HTML) |
