Analysis of microarrays incorporating adjustments for spatial effects

Abstract

Various models were used to extract spatial effects from microarray data. Large discrepancies between the rankings of genes for the different methods were found, due to the roughness of the signal. Models assuming separability and autocorrelation did not perform as well as wavelets because the data were fractal in dimension, so assumptions underlying those models were violated