Statistical issues in the analysis of Illumina data

Background: Illumina bead-based arrays are becoming increasingly popular due to their high degree of replication and reported high data quality. However, little attention has been paid to the pre-processing of Illumina data. In this paper, we present our experience of analysing the raw data from an Illumina spike-in experiment and offer guidelines for those wishing to analyse expression data or develop new methodologies for this technology. Results: We find that the local background estimated by Illumina is consistently low, and subtracting this background is beneficial for detecting differential expression (DE). Illumina's summary method performs well at removing outliers, producing estimates which are less biased and are less variable than other robust summary methods. However, quality assessment on summarised data may miss spatial artefacts present in the raw data. Also, we find that the background normalisation method used in Illumina's proprietary software (BeadStudio) ...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Mark J. Dunning, Nuno L. Barbosa-Morais, Andy G. Lynch, Simon Tavaré, Matthew E. Ritchie
• Keywords: BMCBI 2008, Illumina Bead-based Arrays, Illumina Data, Raw Data