Abstract
Illumina whole-genome expression BeadArrays are a popular choice in gene profiling studies. Aside from the vendor-provided software tools for analyzing BeadArray expression data (GenomeStudio/BeadStudio), there exists a comprehensive set of open-source analysis tools in the Bioconductor project, many of which have been tailored to exploit the unique properties of this platform. In this article, we explore a number of these software packages and demonstrate how to perform a complete analysis of BeadArray data in various formats. The key steps of importing data, performing quality assessments, preprocessing, and annotation in the common setting of assessing differential expression in designed experiments will be covered.
Highlights
Microarrays are a standard laboratory technique for high-throughput gene expression profiling in genomics research
There is a rich literature on the analysis of gene expression microarrays, and while the main steps of an analysis such as quality assessment and normalization still apply, BeadArray data present a number of unique opportunities that may not be fully exploited by standard microarray analysis workflows
Recommended Approach Examine scanner metrics Median background subtraction log2 BASH Examine image plots & boxplots Default Illumina method Non background corrected, non normalized, Sample and Control ‘‘Probe Profile’’ tables Examine boxplots of regular & control probes, multi-dimensional scaling (MDS) plots Normal-exponential convolution using negative controls Quantile log2 Mixture model that uses negative controls Based on annotation quality Linear modelling using weights employed by Illumina to extract intensities from the TIFFs and summarize these values within each sample produce good intensity estimates
Summary
Microarrays are a standard laboratory technique for high-throughput gene expression profiling in genomics research. There is a rich literature on the analysis of gene expression microarrays (see Smyth et al 2003 [2], Allison et al 2006 [3], or Reimers 2010 [4] for reviews), and while the main steps of an analysis such as quality assessment and normalization still apply, BeadArray data present a number of unique opportunities that may not be fully exploited by standard microarray analysis workflows. These include a high and variable level of intra-array replication of probes and a large set of negative controls. Quality assessment Local background adjustment Transformation Spatial artefact detection & removal Quality assessment Summarization Data export from BeadStudio/ GenomeStudio
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