compare {pKSEA}

Running analysis runs on known substrates, predicted substrates, and both.

Description

Performs up to three run_on_matched() runs on summary-prediction matcheddata from get_matched_data(), returning permutation significance score results. If a KSEA database is provided for filtering and comparison, one full analysis will be performed on all phosphosites, one on data with all known kinase substrates removed according to the provided KSEA database, and one on known kinase substrates only.

Usage

compare(matched_data, predictionDB, kseadb, ...)

Arguments

matched_data

File path to summary statistic phosphoproteomics CSV data file with an entry for each phosphopeptide. Required data file columns: GN = gene name identifier that will be matched with prediction database, Peptide = unique peptide identifier (for example, sequence with modifications), Phosphosites = comma-separated phosphorylation sites (eg. "T102,S105"), pval= pairwise test p-value, fc= mean fold change, t= pairwise test t-statistic. pval and fc are used for results reporting only, all others are important for database searching, calculation, and permutation testing.

predictionDB

Input database whose prediction scores will be used for calculations. Required columns: substrate_name= name of substrate corresponding to GN in summary_data, kinase_id = identifiers for kinase predictors, position= phosphorylated residue number, score = numeric score for strength of prediction.

kseadb

Optional KSEA database for filtering purposes. Containing substrate gene name "SUB_GENE" and phosphorylated residue "SUB_MOD_RSD" in standard form (ie. T302).

...

optional parameters to be passed on to downstream functions, including (default): n_permutations (1000), seed (123), kin_ens_table (NULL). See run_on_matched for details.

Examples

#Read in example summary statistics dataset from csv
summarydata_ex <- read.csv(system.file("extdata", "example_data1.csv", package="pKSEA"))

#Get matched data using predictions from NetworKIN
matched_data_ex <- get_matched_data(summarydata_ex, NetworKINPred_db)

#Perform comparative analysis using provided KSEAdb as filter
## Not run: 
compare_results_ex <- compare(matched_data_ex, kseadb = KSEAdb, n_permutations = 10)

## End(Not run)