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Related Concept Videos

DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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Pipeline for macro- and microarray analyses.

R Vicentini1, M Menossi

  • 1Laboratório de Genoma Funcional, Centro de Biologia Molecular e Engenharia Genética, Universidade Estadual de Campinas, Campinas, SP, Brasil.

Brazilian Journal of Medical and Biological Research = Revista Brasileira De Pesquisas Medicas E Biologicas
|April 28, 2007
PubMed
Summary

The Pipeline for Macro- and Microarray Analyses (PMmA) software analyzes DNA array data, identifying nearly 90% of differentially expressed genes. This tool discovered 30 cold-responsive genes in sugarcane, improving upon previous analyses.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • DNA microarray technology generates large datasets for gene expression analysis.
  • Existing analysis methods may not fully account for data variability, potentially missing significant findings.
  • A robust and accessible pipeline is needed for efficient and accurate array data analysis.

Purpose of the Study:

  • To develop and present the Pipeline for Macro- and Microarray Analyses (PMmA) software.
  • To provide a platform-independent tool for analyzing DNA array data.
  • To improve the identification of differentially expressed genes, particularly in response to environmental stimuli.

Main Methods:

  • PMmA is a set of PERL scripts with a web interface, incorporating R for statistical functions.
  • It operates as a five-class pipeline: data format, normalization, data analysis, clustering, and array maps.
  • The software can function as a standalone tool, a BioArray Software Environment plugin, or a local web service.

Main Results:

  • PMmA correctly selects nearly 90% of differentially expressed genes, outperforming other methods.
  • Application to sugarcane cold-stress data identified 30 previously unknown cold-responsive genes.
  • Fourteen genes were upregulated, 14 downregulated, and 2 showed variable expression under cold treatment.

Conclusions:

  • PMmA offers a superior statistical approach for DNA array data analysis.
  • The software enhances the discovery of biologically significant genes, such as those involved in stress response.
  • PMmA is available as a free, platform-independent resource for non-commercial users.