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Related Experiment Videos

Cross platform microarray analysis for robust identification of differentially expressed genes.

Roberta Bosotti1, Giuseppe Locatelli, Sandra Healy

  • 1Genomics Unit, Biotechnology Department, Nerviano Medical Sciences S,r,l, Viale Pasteur 10, 20014 Nerviano, MI, Italy. roberta.bosotti@nervianoms.com

BMC Bioinformatics
|April 14, 2007
PubMed
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Combining Affymetrix (AFFX) and Applied Biosystems (ABI) microarray platforms enhances the identification of robust gene expression changes. Cross-platform validation confirmed substantial agreement, accelerating reliable discovery of differentially expressed genes.

Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Microarrays are widely used for gene expression analysis with multiple commercial platforms available.
  • Combining platforms can overcome individual biases and complement RT-PCR for robust gene expression profiling.
  • This study focuses on cross-platform validation of Affymetrix (AFFX) and Applied Biosystems (ABI) oligonucleotide technologies.

Purpose of the Study:

  • To perform cross-platform validation of two oligonucleotide-based microarray technologies: Affymetrix (AFFX) and Applied Biosystems (ABI).
  • To identify differentially expressed genes using statistical and functional analysis.
  • To assess the agreement and reliability of gene expression data obtained from multiple platforms.

Main Methods:

  • Analysis of gene expression in an ovarian carcinoma cell line treated with a cell cycle inhibitor versus control.

Related Experiment Videos

  • Utilized Affymetrix (AFFX) and Applied Biosystems (ABI) platforms to analyze expression of 16425 genes.
  • Assessed reproducibility using CAT plots and applied integrative correlation analysis for cross-study reproducibility.

    • Main Results:

    • High reproducibility was observed for both platforms, with better scores for AFFX.
    • Identified 930 differentially expressed genes on AFFX and 908 on ABI, with approximately 80% overlap.
    • 62 out of 66 differentially expressed genes identified by microarray were confirmed by RT-PCR, demonstrating high validation rates.

    Conclusions:

    • Cross-platform validation of AFFX and ABI technologies shows good reproducibility and substantial agreement in identifying differentially expressed genes.
    • Pathway analysis revealed biologically relevant signatures consistent with cell cycle inhibition.
    • Combining platforms effectively overcomes platform-specific biases, accelerating the identification of trustworthy differentially expressed genes.