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Related Experiment Videos

Analysis of microarray data using Z score transformation.

Chris Cheadle1, Marquis P Vawter, William J Freed

  • 1DNA Array Unit, Research Resources Branch, National Institute on Aging, National Institutes of Health, Baltimore, Maryland 21221, USA.

The Journal of Molecular Diagnostics : JMD
|April 23, 2003
PubMed
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Z score transformation is a simple method for standardizing gene expression data from high-throughput cDNA microarrays. This normalization allows for reliable comparison of data across experiments and aids in identifying significant gene expression changes.

Area of Science:

  • Bioinformatics
  • Genomics
  • Molecular Biology

Background:

  • High-throughput cDNA microarray technology enables simultaneous gene expression analysis for thousands of genes.
  • There is a need for rapid, simple methods to store, analyze, and compare microarray data.

Purpose of the Study:

  • To evaluate Z score transformation as a method for normalizing microarray data.
  • To compare the effectiveness of Z score transformation with other methods for identifying significant gene expression changes.

Main Methods:

  • Applied Z score transformation for data normalization.
  • Compared Z scores with fold changes, Z ratios, and Z and t statistical tests for significance estimation.

Main Results:

Related Experiment Videos

  • Z score transformation standardizes gene expression data across experiments, independent of hybridization intensities.
  • Normalized data facilitates direct calculation of significant gene expression changes.
  • Z score transformation combined with Z ratios or Z tests provides a rigorous method for basic microarray data analysis.

    • Conclusions:

    • Z score transformation is a useful method for basic microarray data analysis.
    • This method is easily adaptable to standard spreadsheet programs.
    • The results are comparable in rigor to other methods and less arbitrary.