Empirical Bayes models for multiple probe type microarrays at the probe level

Background: When analyzing microarray data a primary objective is often to find differentially expressed genes. With empirical Bayes and penalized t-tests the sample variances are adjusted towards a global estimate, producing more stable results compared to ordinary t-tests. However, for Affymetrix type data a clear dependency between variability and intensity-level generally exists, even for logged intensities, most clearly for data at the probe level but also for probe-set summarizes such as the MAS5 expression index. As a consequence, adjustment towards a global estimate results in an intensity-level dependent false positive rate. Results: We propose two new methods for finding differentially expressed genes, Probe level Locally moderated Weighted median-t (PLW) and Locally Moderated Weighted-t (LMW). Both methods use an empirical Bayes model taking the dependency between variability and intensitylevel into account. A global covariance matrix is also used allowing for differing var...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Magnus Åstrand, Petter Mostad, Mats Rudemo
• Keywords: BMCBI 2008, Empirical Bayes, Expressed Genes, Global Estimate