This is a wrapper implementation of RUVIII for phosphoproteomics data normalisation. This function will call tailImpute function to impute all the missing values (if there is any) in the phosphoproteomics data for applying RUVIII. It will then return the normalised values for quantified phosphosites and remove imputed values.
RUVphospho( mat, M, ctl, k = NULL, m = 1.6, s = 0.6, keepImpute = FALSE, assay = NULL, ... )
a matrix (or PhosphoExperiment object) with rows correspond to phosphosites and columns correspond to samples.
is the design matrix as defined in RUVIII.
is the stable phosphosites (or negative controls as defined in RUVIII).
is the number of unwanted factors as defined in RUVIII.
a numeric number for controlling mean downshifting.
a numeric number for controlling standard deviation of downshifted sampling values.
a boolean to keep the missing value in the returned matrix.
an assay to be selected if
mat is a PhosphoExperiment
additional parameters that may be passed to RUVIII.
A normalised matrix.
data('phospho_L6_ratio_pe') data('SPSs') grps = gsub('_.+', '', colnames(phospho.L6.ratio.pe)) 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 = "") # Construct a design matrix by condition design = model.matrix(~ grps - 1) # phosphoproteomics data normalisation using RUV ctl = which(L6.sites %in% SPSs) phospho.L6.ratio.RUV = RUVphospho( SummarizedExperiment::assay(phospho.L6.ratio.pe, "Quantification"), M = design, k = 3, ctl = ctl)