Informatics and Statistics for Analyzing 2-D Gel Electrophoresis Images

Andrew Dowsey, J S Morris, G Z Yang, M J Dunn

Research output: Chapter in Book/Report/Conference proceedingChapter in a book

12 Citations (Scopus)

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.
Original languageEnglish
Title of host publicationProteome Bioinformatics
EditorsSimon J Hubbard, Andrew R Jones
Place of PublicationNew York
PublisherSpringer
Pages239-255
Number of pages17
ISBN (Electronic)9781607614449
ISBN (Print)9781607614432
DOIs
Publication statusPublished - 2010

Publication series

NameMethods in Molecular Biology™
PublisherSpringer
Volume604

Keywords

  • 2-D gel electrophoresis
  • Image alignment
  • Spot detection
  • Spot matching
  • Differential expression analysis
  • Clustering
  • DIGE

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