standardise.Rd
Standardisation by z-score transformation.
standardise(mat)
A standardised matrix
data('phospho_L6_ratio_pe')
data('SPSs')
grps = gsub('_.+', '', colnames(phospho.L6.ratio.pe))
# Construct a design matrix by condition
design = model.matrix(~ grps - 1)
# phosphoproteomics data normalisation using RUV
L6.sites = paste(sapply(GeneSymbol(phospho.L6.ratio.pe), function(x)paste(x)),
";",
sapply(Residue(phospho.L6.ratio.pe), function(x)paste(x)),
sapply(Site(phospho.L6.ratio.pe), function(x)paste(x)),
";", sep = "")
ctl = which(L6.sites %in% SPSs)
phospho.L6.ratio.pe = RUVphospho(phospho.L6.ratio.pe,
M = design, k = 3,ctl = ctl)
phosphoL6 = SummarizedExperiment::assay(phospho.L6.ratio.pe, "normalised")
# filter for up-regulated phosphosites
phosphoL6.mean <- meanAbundance(phosphoL6, grps = grps)
aov <- matANOVA(mat=phosphoL6, grps = grps)
phosphoL6.reg <- phosphoL6[(aov < 0.05) &
(rowSums(phosphoL6.mean > 0.5) > 0),,drop = FALSE]
L6.phos.std <- standardise(phosphoL6.reg)