Error, reproducibility and sensitivity : a pipeline for data processing of Agilent oligonucleotide expression arrays

Background: Expression microarrays are increasingly used to obtain large scale transcriptomic information on a wide range of biological samples. Nevertheless, there is still much debate on the best ways to process data, to design experiments and analyse the output. Furthermore, many of the more sophisticated mathematical approaches to data analysis in the literature remain inaccessible to much of the biological research community. In this study we examine ways of extracting and analysing a large data set obtained using the Agilent long oligonucleotide transcriptomics platform, applied to a set of human macrophage and dendritic cell samples. Results: We describe and validate a series of data extraction, transformation and normalisation steps which are implemented via a new R function. Analysis of replicate normalised reference data demonstrate that intrarray variability is small (only around 2% of the mean log signal), while interarray variability from replicate array measurements has ...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Benjamin Chain, Helen Bowen, John Hammond, Wilfried Posch, Jane Rasaiyaah, Jhen Tsang, Mahdad Noursadeghi
• Keywords: Biological Research Community, BMCBI 2010, Dendritic Cell Samples, Scale Transcriptomic Information