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Illumina WG-6 BeadChip strips should be normalized separately.

Wei Shi1, Ashish Banerjee, Matthew E Ritchie

  • 1Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, VIC 3052, Australia. shi@wehi.edu.au

BMC Bioinformatics
|November 12, 2009
PubMed
Summary

Strip-level normalization improves gene expression analysis on Illumina Sentrix-6 Whole-Genome Expression BeadChips by addressing between-strip variation. This enhanced precision increases detected genes and strengthens biological conclusions.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Microarray Technology

Background:

  • Illumina Sentrix-6 Whole-Genome Expression BeadChips present unique normalization challenges due to their design of six microarrays, each with two physical strips.
  • Existing normalization strategies for this platform do not account for potential systematic variation between these two strips within an array.

Purpose of the Study:

  • To investigate the impact of strip-level versus array-level normalization on Illumina Sentrix-6 BeadChip data.
  • To demonstrate a method for improving the precision and biological relevance of gene expression measurements.

Main Methods:

  • Development and application of strip-level normalization techniques.
  • Comparison of strip-level normalization against array-level normalization strategies.

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  • Utilizing proposed plots to identify intensity range inconsistencies between strips.

    • Main Results:

    • Strip-level normalization effectively removes between-strip variation, enhancing gene expression measurement precision.
    • A 20% increase in statistical information and a doubling of detected genes at a 5% false discovery rate were observed with strip-level normalization.
    • Functional analysis confirmed that the additional genes identified through strip-level normalization possess significant biological relevance.

    Conclusions:

    • Strip-level normalization is recommended for Illumina Sentrix-6 BeadChip preprocessing when inter-strip intensity ranges are inconsistent.
    • Proposed plots visually demonstrate the necessity of strip-level normalization based on intensity range variations.
    • Provided R code facilitates the implementation of recommended plots and normalization algorithms for strip-level analysis.