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Related Experiment Videos

RefPlus: an R package extending the RMA Algorithm.

Chris Harbron1, Kai-Ming Chang, Marie C South

  • 1Statistical Sciences, AstraZeneca, Alderley Park, Macclesfield, Cheshire SK10 4TG, UK. Chris.Harbron@AstraZeneca.Com

Bioinformatics (Oxford, England)
|July 12, 2007
PubMed
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The RefPlus package introduces new algorithms to address limitations in Robust Multi-array Analysis (RMA) for gene expression microarrays. These methods ensure consistent probeset intensities, even with added data, improving data analysis reproducibility.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Robust Multi-array Analysis (RMA) is a standard for Affymetrix microarray preprocessing.
  • A key limitation of RMA is the instability of probeset intensities when new microarrays are added to an analysis set.
  • This instability can affect the reproducibility and reliability of gene expression studies.

Purpose of the Study:

  • To introduce novel algorithms that overcome the limitations of RMA.
  • To provide a software package for implementing these new algorithms.
  • To ensure consistent and reliable gene expression data analysis.

Main Methods:

  • Development of the Extrapolation Strategy algorithm.
  • Development of the Extrapolation Averaging algorithm.

Related Experiment Videos

  • Implementation of these algorithms within the RefPlus R package.

    • Main Results:

    • The RefPlus package offers functions for Extrapolation Strategy and Extrapolation Averaging.
    • These algorithms address the issue of changing probeset intensities when microarrays are re-processed.
    • The implemented methods ensure stable and reproducible gene expression data.

    Conclusions:

    • The RefPlus package provides a robust solution for Affymetrix microarray preprocessing.
    • The Extrapolation Strategy and Extrapolation Averaging algorithms enhance data consistency.
    • This improves the reliability of gene expression profiling studies.