Informatics and Statistics for Analyzing 2-D Gel Electrophoresis Images

Despite recent progress in “shotgun” peptide separation by integrated liquid chromatography and mass spectrometry (LC/MS), proteome coverage and reproducibility are still limited with this approach and obtaining enough replicate runs for biomarker discovery is a challenge. For these reasons, recent research demonstrates that there is a continuing need for protein separation by two-dimensional gel electrophoresis (2-DE). However, with traditional 2-DE informatics, the digitized images are reduced to symbolic data through spot detection and quantification before proteins are compared for differential expression by spot matching. Recently, a more robust and automated paradigm has emerged where gels are directly aligned in the image domain before spots are detected across the whole image set as a whole. In this chapter, we describe the methodology for both approaches and discuss the pitfalls present when reasoning statistically about the differential protein expression discovered.