When obtaining high-throughput data from antibody arrays, researchers have to face a couple of questions: How and by what means can they get reasonable results significant to their research from these data? Similar to a gene microarray, the classical statistical pipeline of an antibody array includes data preprocessing transformation, differential expression analysis, classification, and biological annotation analysis. In this chapter, we will provide a pipeline of statistical approaches suitable for antibody arrays to facilitate better understanding of the results gained from each of these steps.
Keywords: Data preprocess; Differential expression analysis; Gene ontology; KEGG; Supervised classification; Unsupervised classification.