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Motivation: Microarray results accumulated in public repositories are widelyre-used in meta-analytical studies and secondary databases. The quality of thedata obtained with this technology varies from experiment to experiment andefficient method for quality assessment is neces-sary to ensure theirreliability. Results: The lack of a good benchmark has hampered evaluation ofexisting methods for quality control. In this study we propose a newinde-pendent quality metric that is based on evolutionary conservation ofexpression profiles. We show, using 11 large organ-specific datasets, thatIQRray, a new quality metrics developed by us, exhibits the highest correlationwith this reference metric, among 14 metrics tested. IQRray outperforms othermethods in identification of poor quality arrays in dataset composed of arraysfrom many independent experiments. In con-trast, the performance of methodsdesigned for detecting outliers in a single experiment like NUSE and RLE waslow because of the inability of these method to detect datasets containing onlylow quality arrays, and the fact that the scores cannot be directly comparedbetween ex-periments. Availability: The R implementation of IQRray is availableat: ftp://lausanne.isb-sib.ch/pub/databases/Bgee/general/IQRray.R

IQRray, a new method for Affymetrix microarray quality control, and the  homologous organ conservation score, a new benchmark method for quality  control metrics