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Related Experiment Videos

Spotting effect in microarray experiments.

Tristan Mary-Huard1, Jean-Jacques Daudin, Stéphane Robin

  • 1Institut National Agronomique Paris-Grignon, 75231 Paris, France. maryhuar@inapg.fr

BMC Bioinformatics
|May 21, 2004
PubMed
Summary

A newly identified spatial variability, the "spotting effect," impacts microarray data from Cy3/Cy5 spotted glass arrays. Current normalization methods fail to correct this bias, potentially skewing analysis results.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Microarray Technology

Background:

  • Microarray data requires normalization due to inherent biases.
  • Spatial experimental variability significantly affects Cy3/Cy5 spotted glass array data.
  • This variability introduces periodic patterns in signal ratio and intensity across arrays.

Purpose of the Study:

  • To identify and characterize a source of spatial variability in microarray data.
  • To assess the impact of this variability on data analysis.
  • To evaluate the effectiveness of existing normalization methods.

Main Methods:

  • Utilized geostatistical tools, specifically the variogram, to analyze spatial patterns.
  • Characterized the observed variability, termed the "spotting effect."

Related Experiment Videos

  • Investigated the origin of the spotting effect during array printing.

    • Main Results:

    • Identified a significant source of spatial experimental variability in microarray data.
    • The "spotting effect" manifests as a periodic pattern affecting signal and intensity.
    • Geostatistical analysis using variograms effectively characterized this spatial bias.

    Conclusions:

    • The "spotting effect" is a novel bias affecting Cy3/Cy5 spotted glass arrays.
    • Current normalization techniques, including those for spatial variability, do not adequately correct the spotting effect.
    • The spotting effect can significantly alter downstream analyses such as differential and clustering analysis.