Supplementary Figure 1 : Precision of the phosphoproteomics workflow.

From: High-throughput phosphoproteomics reveals in vivo insulin signaling dynamics

Supplementary Figure 1

Two identical SILAC-labelled HeLa cell populations were mixed a immediately after cell scraping or b after the phosphorylation enrichment workflow and immediately before LC-MS analysis. c-d Distribution and standard deviations of SILAC ratios of phosphopeptides from the experiments shown in the panel above are shown. e Sources of variability in phosphoproteome platform (1) biological, (2) workflow, or (3) LC-MS, investigated by replicates at each level as indicated. f Box-plot of Coefficient of Variation (%) of phosphopeptide intensities calculated from replicate sample data in e. g Average Pearson correlation coefficients (in box inset) for the replicate experiments, and density plots depicting the log2 transformed intensities of two representative replicates. Representative samples shown in plots were chosen based on the closest match between pairwise correlation coefficients and average correlation coefficients for all replicates. h Performance of match between runs (MBR) in transferring identification of phosphopeptides and quantification between replicate workflow samples. Percent valid values are calculated by dividing the number of unique phosphopeptides quantified in all replicates by the total number of possible quantification points, i.e. (∑ phosphopeptides quantified / (total number of phosphopeptides identified x number of replicates)) x 100). Error bars denote SD.