Abstract
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.
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Dowsey, A.W., Morris, J.S., Gutstein, H.B., Yang, GZ. (2010). Informatics and Statistics for Analyzing 2-D Gel Electrophoresis Images. In: Hubbard, S., Jones, A. (eds) Proteome Bioinformatics. Methods in Molecular Biology™, vol 604. Humana Press. https://doi.org/10.1007/978-1-60761-444-9_16
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DOI: https://doi.org/10.1007/978-1-60761-444-9_16
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