creedenzymatic_analysis.R

# Creedenzymatic Analysis

library(tidyverse)
library(creedenzymatic)

process_creedenzymatic <-
    function(krsa_path, uka_path, peptide_path) {
        krsa_data <- read_csv(krsa_path, show_col_types = FALSE) |>
            select(Kinase, Score = AvgZ) |>
            read_krsa(trns = "abs", sort = "desc")

        uka_data <- read_tsv(uka_path, show_col_types = FALSE) |>
            select(Kinase = `Kinase Name`, Score = `Median Final score`) |>
            read_uka(trns = "abs", sort = "desc")

        peptide_data <-
            read_csv(peptide_path, show_col_types = FALSE) |>
            select(Peptide, Score = totalMeanLFC)

        kea3_data <-
            read_kea(
                peptide_data,
                sort = "asc",
                trns = "abs",
                method = "MeanRank",
                lib = "kinase-substrate"
            )

        ptmsea_data <-
            read_ptmsea(peptide_data)

        combined <- combine_tools(
            KRSA_df = krsa_data,
            UKA_df = uka_data,
            KEA3_df = kea3_data,
            PTM_SEA_df = ptmsea_data
        )

        combined
    }

krsa_files <- c("results/withinChip_KRSA_Table_GLU_VEH.csv")

uka_files <- c("kinome_data/UKA/Summaryresults 20220406-1355.txt")

peptide_files <- c("results/dpp_GLU_VEH-STK.csv")

result <-
    list(krsa_path = krsa_files,
         uka_path = uka_files,
         peptide_path = peptide_files) |>
    pmap(process_creedenzymatic) |>
    set_names("Glutamate") |>
    imap_dfr(~ write_csv(.x, str_glue("results/{.y}_creedenzymatic.csv")), .id = "Comparison")