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Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

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Comments on sequence normalization of tiling array expression.

Don Gilbert1, Andreas Rechtsteiner

  • 1Department of Biology, Indiana University, Bloomingto, IN, USA. gilbertd@indiana.edu

Bioinformatics (Oxford, England)
|July 7, 2009
PubMed
Summary
This summary is machine-generated.

Statistical normalization of tiling array expression signals using probe sequence content does not improve gene detection. This method confounds probe sequence with gene structure, obscuring important signals at gene boundaries.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Gene Expression Analysis

Background:

  • Accurate detection of genome features requires improved tiling array expression signal analysis.
  • Existing methods for signal normalization need independent verification.

Purpose of the Study:

  • To independently verify statistical normalization methods for tiling array expression signals based on probe sequence content.
  • To assess the efficacy of sequence content normalization in improving gene detection.

Main Methods:

  • Analysis of probe sequence content in tiling array data.
  • Statistical normalization procedures applied to tile signals.
  • Assessment of normalization impact on detecting gene structures (introns/exons).

Main Results:

  • Sequence content normalization confounded probe sequence with gene structure (intron/exon) content.
  • Normalization obscured tile signal changes at gene structure boundaries.
  • Simple sequence normalization did not enhance the detection of genes from expression data.

Conclusions:

  • The tested sequence content normalization methods do not improve gene detection accuracy from tiling array data.
  • Confounding of probe and gene structure sequences limits the utility of this normalization approach.
  • Further development is needed for accurate genome feature detection using tiling arrays.