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. Author manuscript; available in PMC: 2013 Sep 1.
Published in final edited form as: Methods Mol Biol. 2010;673:211–222. doi: 10.1007/978-1-60761-842-3_13

Fig. 4.

Fig. 4

(a) The distribution that represents the null hypothesis, that is, that a given ratio is random. This distribution can be obtained by analysis of samples where only random variation is expected (technical and biological replicates). Then the significance of a ratio measurement can be calculated by integrating this distribution from the measured ratio to infinity. (b–g) Combining data from repeat analysis makes the distribution that represents the null hypothesis narrower, and smaller changes can be detected. Examples of the effect of replicate analysis on the protein ratio distribution for a workflow comprising immunoprecipitation, protein fractionation, and digestion (simulated data based on measurements of the variation in the individual steps) (26). Only limited improvements are observed beyond 3, 3, 1 repeat analyses for immunoprecipitation, protein fractionation and digestion, respectively (solid curves). Dotted curves: (b) 1, 1, 1; (c) 1, 3, 1; d () 3, 1, 1; (e) 3, 3, 3; (f) 3, 6, 1; (g) 6, 3, 1 repeat analyses for immunoprecipitation, protein fractionation and digestion, respectively.