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Analysis of probe level patterns in Affymetrix microarray data.

Alexander C Cambon1, Abdelnaby Khalyfa, Nigel G F Cooper

  • 1Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, University of Louisville, Louisville, Kentucky, USA. accamb01@louisville.edu <accamb01@louisville.edu>

BMC Bioinformatics
|May 8, 2007
PubMed
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Analyzing Affymetrix Genechip microarray data reveals probe variability. Examining probe-level intensities helps refine conclusions about differentially expressed genes, improving real-time PCR analysis.

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Microarrays enable parallel analysis of thousands of gene expression profiles.
  • Common methods like RMA and GCRMA summarize probe intensities into single expression measures.
  • Alternative methods analyze probe intensities directly, bypassing summarization.

Purpose of the Study:

  • To explore variability in probe response patterns within transcripts using Affymetrix rat genome Genechip.
  • To identify sources of variability in probe sets, including probe location, sequence, homology, and affinity.

Main Methods:

  • Utilized Affymetrix rat genome Genechip for expression analysis.
  • Investigated probe-level data for sources of variability.
  • Performed BLAST searches to assess sequence homology.

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Main Results:

  • Probe location, middle base pair, and affinity effects contribute minimally to gene-level variation.
  • High sequence homology was observed between probes and non-target genes.
  • Probe by treatment interactions were identified for differentially expressed genes.

Conclusions:

  • Modeling probe-level intensities aids in refining conclusions about differential gene expression.
  • Understanding probe variability is crucial for accurate gene expression analysis.
  • Implications for probe sequence selection in real-time PCR (RT-PCR) are discussed.