CoPhosK: A method for comprehensive kinase substrate annotation using co-phosphorylation analysis
Fig 7
Consistency and reproducibility of kinase-substrate predictions made using different phosphorylation data sets.
For each phosphosite in each data set, we rank the kinases using CophosK+, and then we identify the top ranked kinase based on two different datasets. (a) The Venn diagrams show (1) the number of phosphosites for which top-ranked kinase agrees with that reported in PhosphoSitePlus (True Positive), (2) the number of phosphosites that have kinases reported in PhosphoSitePlus but top-ranked kinase does not agree with that reported in PhosphoSitePlus (False Positive), and (3) the number of phosphosites with no kinase annotation reported in PhosphoSitePlus. The blue circles represent predictions based on ovarian cancer tumor cell lines, pink circles represents predictions based on breast cancer PDX. For the phosphosites for which at least one kinase is listed in PhosphoSitePlus, the right panel shows the “precision” (True Positive / (True Positive + False Positive)) of the top ranked kinase for each individual dataset and the intersection between the two datasets (i.e., the same kinase is ranked top in both datasets). (b) The number of phosphosites with at least one annotation in PhosphoSitePlus (upper panel) and no annotation in PhosphoSitePlus (lower panel) are shown as a function of the number of datasets that contain the phosphosite. Among these phosphosites, the number of phosphosites for which the top ranked kinase is identical across multiple datasets (identical predicted KSAs) is also shown as a function of the number of supporting datasets. For the phosphosites with annotations, the number of predictions that are consistent with PhosphositePlus annotations are also shown (true identical KSAs).