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High-sensitivity transcriptome data structure and implications for analysis and biologic interpretation.

Sebastian Noth1, Guillaume Brysbaert, François-Xavier Pellay

  • 1Systems Epigenomics Group, Institut des Hautes Etudes Scientifiques/Institut de Recherches Interdisciplinaires, CNRS/INSERM, 91440 Bures sur Yvette, France.

Genomics, Proteomics & Bioinformatics
|May 29, 2007
PubMed
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The AB1700 microarray platform offers enhanced sensitivity for detecting weakly expressed transcripts, extending the dynamic range. Analysis reveals a dual lognormal distribution, necessitating new methods for high-sensitivity transcriptome data.

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Novel microarray technologies aim to improve transcript detection sensitivity and dynamic range.
  • The Applied Biosystems AB1700 platform is a new technology with enhanced capabilities.

Purpose of the Study:

  • To compare the AB1700 platform data with Affymetrix HG-U133A data.
  • To analyze the statistical properties of AB1700 data for method development.

Main Methods:

  • Comparative analysis of AB1700 and Affymetrix HG-U133A datasets.
  • Statistical modeling of signal distribution and variance in AB1700 data.

Main Results:

  • The AB1700 platform extends the signal dynamic range by one order of magnitude at the lower bound.

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  • AB1700 data exhibits a dual lognormal signal distribution, capturing previously undetected transcripts.
  • A signal variance distribution model was derived for AB1700 data.

    • Conclusions:

    • The unique statistical properties of AB1700 data require adaptation of existing microarray analysis methods.
    • The dual lognormal distribution may indicate distinct biological mechanisms of transcription initiation.