Computational analysis of quantitative proteomics data using stable isotope labeling.
Over the last few years, new proteomics methods have been developed for making quantitative comparisons using stable isotope labeling. Although these methods have paved the way for quantitative proteomics, the analysis of these data is often the rate-limiting step. In fact, many analyzes are still carried out manually, which adds a level of subjectivity to the data that will vary between laboratories and even analysts. In this chapter, we have attempted to summarize several of the key steps necessary for an individual to automate the analysis of quantitative proteomics data. The approach is straightfoward to implement for an individual with moderate programming experience and used to process proteomics data in an objective manner.
MacCoss
Michael J
MJ
Department of Genome Sciences, University of Washington, Seattle, USA.
Wu
Christine C
CC
D000818:Animals; D002853:Chromatography, Liquid; D019295:Computational Biology / Q000379:methods*; D001330:Electronic Data Processing / Q000379:methods*; D007553:Isotope Labeling / Q000379:methods*; D010455:Peptides / Q000737:chemistry; D040901:Proteomics / Q000379:methods*; D051381:Rats; D012984:Software; D053719:Tandem Mass Spectrometry
D010455:Peptides