Cross platform microarray analysis for robust identification of differentially expressed genes
2007

Cross-Platform Microarray Analysis for Identifying Differentially Expressed Genes

Sample size: 66 publication 10 minutes Evidence: high

Author Information

Author(s): Roberta Bosotti, Giuseppe Locatelli, Sandra Healy, Emanuela Scacheri, Luca Sartori, Ciro Mercurio, Raffaele Calogero, Antonella Isacchi

Primary Institution: Nerviano Medical Sciences S.r.l.

Hypothesis

Can the combined use of multiple microarray platforms improve the identification of differentially expressed genes?

Conclusion

The study demonstrates that both Affymetrix and Applied Biosystems platforms can reliably identify differentially expressed genes with substantial agreement.

Supporting Evidence

  • 930 genes were identified as differentially expressed on Affymetrix and 908 on Applied Biosystems, with ~80% common to both platforms.
  • 62 out of 66 genes identified as differentially expressed by microarray were confirmed by RT-PCR.
  • Both platforms showed high reproducibility with R squared values >0.99 for Affymetrix and >0.94 for Applied Biosystems.

Takeaway

Researchers used two different methods to study genes in cancer cells and found that using both methods together helps to find more accurate results.

Methodology

The study involved analyzing gene expression in ovarian cancer cells treated with a cell cycle inhibitor using two microarray platforms and validating results with RT-PCR.

Potential Biases

Differences in probe design and technical features between platforms could introduce bias.

Limitations

The study may not account for all potential biases inherent in different microarray technologies.

Participant Demographics

Ovarian carcinoma cell line A2780 was used for the experiments.

Statistical Information

P-Value

<0.5

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.1186/1471-2105-8-S1-S5

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