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AffyGCQC: a web-based interface to detect outlying genechips with extreme studentized deviate tests.

José Osorio Y Fortéa1, Eric Prina, Thierry Lang

  • 1Unité d'Immunophysiologie et Parasitisme Intracellulaire, Département de Parasitologie et Mycologie, Institut Pasteur, 25 rue du Docteur Roux, 75724 Paris, France. josorio@pasteur.fr

Journal of Bioinformatics and Computational Biology
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PubMed
Summary

A new bioinformatics tool, AffyGCQC, offers objective outlier detection for Affymetrix GeneChip quality control. This web-based program enhances the reliability of gene expression analysis by identifying experimental variability.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Molecular Biology

Background:

  • Affymetrix GeneChip arrays are crucial for analyzing gene expression differences.
  • Data production involves potential variability unrelated to biological signals.
  • Rigorous quality control is essential for meaningful downstream analysis.

Purpose of the Study:

  • To develop a bioinformatics tool for Affymetrix GeneChip Quality Control (AffyGCQC).
  • To provide objective outlier detection for gene expression array experiments.

Main Methods:

  • Implementation of graphical representation for Affymetrix-recommended QC metrics.
  • Application of extreme studentized deviate statistical tests for outlier detection.
  • Development of an easy-to-use web-based interface.

Main Results:

  • AffyGCQC provides graphical QC metrics for Affymetrix arrays.
  • The tool objectively identifies outlier arrays using statistical tests.
  • Facilitates reliable data quality assessment in gene expression studies.

Conclusions:

  • AffyGCQC enhances the reliability of gene expression data analysis.
  • The tool offers an objective approach to quality control for Affymetrix arrays.
  • Web-based accessibility simplifies its implementation in research settings.