kinaseSubstrateScore: Kinase substrate scoring

In PYangLab/PhosR: A set of methods and tools for comprehensive analysis of phosphoproteomics data

Kinase substrate scoring

Description

This function generates substrate scores for kinases that pass filtering based on both motifs and dynamic profiles

Usage

kinaseSubstrateScore(
  substrate.list,
  mat,
  seqs,
  numMotif = 5,
  numSub = 1,
  species = "mouse",
  verbose = TRUE
)

Arguments

substrate.list	A list of kinases with each element containing an array of substrates.
mat	A matrix with rows correspond to phosphosites and columns correspond to samples.
seqs	An array containing aa sequences surrounding each of all phosphosites. Each sequence has length of 15 (-7, p, +7).
numMotif	Minimum number of sequences used for compiling motif for each kinase. Default is 5.
numSub	Minimum number of phosphosites used for compiling phosphorylation profile for each kinase. Default is 1.
species	Motif list species to be used. Currently there are mouse (default), human and rat.
verbose	Default to TRUE to show messages during the progress. All messages will be suppressed if set to FALSE

Value

A list of 4 elements. motifScoreMatrix, profileScoreMatrix, combinedScoreMatrix, ksActivityMatrix (kinase activity matrix) and their weights.

Examples

data('phospho_L6_ratio_pe')
data('SPSs')
data('PhosphoSitePlus')

ppe <- phospho.L6.ratio.pe
sites = paste(sapply(GeneSymbol(ppe), function(x)x),";",
    sapply(Residue(ppe), function(x)x),
    sapply(Site(ppe), function(x)x),
    ";", sep = "")
grps = gsub("_.+", "", colnames(ppe))
design = model.matrix(~ grps - 1)
ctl = which(sites %in% SPSs)
ppe = RUVphospho(ppe, M = design, k = 3, ctl = ctl)

phosphoL6 = SummarizedExperiment::assay(ppe, "normalised")

# filter for up-regulated phosphosites
phosphoL6.mean <- meanAbundance(phosphoL6, grps = grps)
aov <- matANOVA(mat=phosphoL6, grps = grps)
idx <- (aov < 0.05) & (rowSums(phosphoL6.mean > 0.5) > 0)
phosphoL6.reg <- phosphoL6[idx, ,drop = FALSE]

L6.phos.std <- standardise(phosphoL6.reg)

rownames(L6.phos.std) <- paste0(GeneSymbol(ppe), ";", Residue(ppe), 
    Site(ppe), ";")[idx]

L6.phos.seq <- Sequence(ppe)[idx]

L6.matrices <- kinaseSubstrateScore(PhosphoSite.mouse, L6.phos.std,
    L6.phos.seq, numMotif = 5, numSub = 1)

PYangLab/PhosR documentation built on Nov. 1, 2024, 1:47 p.m.