Protein expression microarrays, also called antibody arrays, represent a new technology that allows the expression level of proteins to be assessed directly. As is also the case with gene expression microarrays, it is hoped that protein expression microarrays will aid in biomarker discovery, predicting disease outcomes and response to treatments, and detecting molecular mechanisms and/or pathways associated with a particular disease state. However, accurately achieving these aims is dependent upon suitable experimental designs, normalization procedures that eliminate systematic bias, and appropriate statistical analyses to assess differential expression or expose expression patterns. In the last five years, a large amount of research has been devoted to two-color cDNA arrays to improve experimental design, normalization and statistical analyses to assess differential expression and classification. These methods are directly applicable to two-color antibody arrays. The objective of this article is to discuss statistical methods that have been developed for cDNA arrays and describe how the methods can be directly applied to antibody arrays.