kinaseSubstrateScore {PhosR} | R Documentation |
This function generates substrate scores for kinases that pass filtering based on both motifs and dynamic profiles
kinaseSubstrateScore( substrate.list, mat, seqs, numMotif = 5, numSub = 1, verbose = TRUE )
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. |
verbose |
Default to |
A list of 4 elements.
motifScoreMatrix
, profileScoreMatrix
,
combinedScoreMatrix
, ksActivityMatrix
(kinase activity matrix)
and their weights
.
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)