Algorithm-driven Artifacts in median polish summarization of Microarray data

Background: High-throughput measurement of transcript intensities using Affymetrix type oligonucleotide microarrays has produced a massive quantity of data during the last decade. Different preprocessing techniques exist to convert the raw signal intensities measured by these chips into gene expression estimates. Although these techniques have been widely benchmarked in the context of differential gene expression analysis, there are only few examples where their performance has been assessed in respect to coexpression-based studies such as sample classification. Results: In the present paper we benchmark the three most used normalization procedures (MAS5, RMA and GCRMA) in the context of inter-array correlation analysis, confirming and extending the finding that RMA and GCRMA consistently overestimate sample similarity upon normalization. We determine that median polish summarization is responsible for generating a large proportion of these over-similarity artifacts. Furthermore, we s...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Federico M. Giorgi, Anthony M. Bolger, Marc Lohse, Björn Usadel
• Keywords: BMCBI 2010, Gene Expression, Inter-array Correlation, Massive Quantity