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Applied Mathematics Seminar
Date/Time/Room: Friday (10/6/2006) at 2:00pm in 304 Pickard Hall
Speaker: Dr. Alan R. Dabney, Assistant Professor "Functional ANOVA Normalization of TwoChannel Microarrays"Abstract: We present a new, general method for normalizing twochannel microarray data, partially drawing on ideas from two widely used approaches. Whereas the ANOVA approach carefully distinguishes different sources of signal and bias through explicit terms in its model, the MAplot based approach takes into account the fact that sources of bias may be intensitydependent. However, both approaches suffer from serious drawbacks, as we have shown in previous work. The fixed (nonintensitydependent) coefficients in the ANOVA approach tend to under or overfit the data, and the MAplot based approach assumes that all intensitydependent trends are due to unwanted bias, each leading to inaccurate normalization in fairly common scenarios. Our proposed approach, called eCADS, captures the strengths of these previous approaches, while avoiding their weaknesses. We replace the fixed coefficients in the ANOVA model with functions of underlying RNA amount, thereby incorporating intensitydependent relationships like those evident in MAplots. The normalization method fits this "functional ANOVA" model and subtracts off terms representing bias to retain the biological signal of interest. By requiring a simple balance in experimental design, we show that our method preserves differential expression relationships in expectation. A consequence of this work is the statistical justification of a more efficient dyeswap design that requires only one array per sample pair. We demonstrate our new method on an experiment measuring expression in developing mice.

