Prediction-Based Kinase-Substrate Enrichment Analysis
Running pKSEA::compare() on multiple files
Calculate score contributions by phosphorylation site
Running analysis runs on known substrates, predicted substrates, and b...
Filtering data to matched predictions
Sum score contributions for each kinase across all phosphopeptides
Extract summary table with pertinent columns related to included subst...
Filter matched data to remove positive IDs from KSEA
mk_runlabel()
Get percentile ranks across permutations
Obtain percentile rank comparing a single value to set
Perform permutation test
Output writing of pKSEA compare() results
Runs pKSEA analysis on a dataset result from get_matched_data.
A tool for inferring kinase activity changes from phosphoproteomics data. 'pKSEA' uses kinase-substrate prediction scores to weight observed changes in phosphopeptide abundance to calculate a phosphopeptide-level contribution score, then sums up these contribution scores by kinase to obtain a phosphoproteome-level kinase activity change score (KAC score). 'pKSEA' then assesses the significance of changes in predicted substrate abundances for each kinase using permutation testing. This results in a permutation score (pKSEA significance score) reflecting the likelihood of a similarly high or low KAC from random chance, which can then be interpreted in an analogous manner to an empirically calculated p-value. 'pKSEA' contains default databases of kinase-substrate predictions from 'NetworKIN' (NetworKINPred_db) <http://networkin.info> Horn, et. al (2014) <doi:10.1038/nmeth.2968> and of known kinase-substrate links from 'PhosphoSitePlus' (KSEAdb) <https://www.phosphosite.org/> Hornbeck PV, et. al (2015) <doi:10.1093/nar/gku1267>.