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Mapping Absolute DNA Density in Cell Nuclei using Single-molecule Localization Microscopy
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Identification and correction of previously unreported spatial phenomena using raw Illumina BeadArray data.

Mike L Smith1, Mark J Dunning, Simon Tavaré

  • 1Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK. mike.l.smith@cancer.org.uk

BMC Bioinformatics
|April 29, 2010
PubMed
Summary

Analyzing raw Illumina data can identify and correct spatial phenomena impacting feature intensity extraction. This ensures more accurate microarray analysis by addressing image processing issues that standard data analysis may miss.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Microarray Technology

Background:

  • Accurate feature-intensity extraction is critical for microarray analysis, especially on Illumina BeadArrays due to random bead construction.
  • Image processing issues can significantly compromise downstream analysis, often going unnoticed with standard data.
  • Spatial phenomena can affect feature intensity extraction, necessitating careful examination of raw data.

Purpose of the Study:

  • To demonstrate the identification and potential correction of spatial phenomena affecting feature-intensity extraction in Illumina BeadArray data.
  • To highlight the importance of analyzing raw data for quality control in microarray experiments.

Main Methods:

  • Utilized raw Illumina data to investigate spatial-related phenomena impacting feature-intensity extraction.

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  • Developed diagnostic methods to identify image processing issues and bead location inaccuracies.
  • Explored approaches for correcting identified spatial anomalies.

    • Main Results:

    • Identified spatial phenomena causing unnaturally high feature intensities and non-random bead neighborhood configurations.
    • Highlighted challenges in bead localization and its impact on intensity measurements.
    • Demonstrated that beads can be misidentified on local or array-wide scales, affecting data quality.

    Conclusions:

    • Image processing issues in microarray data often go undetected by standard analysis.
    • Simple diagnostics can identify these problems, and raw data access enables correction.
    • Acquiring raw microarray data is crucial for robust quality control and accurate analysis.