frequencyScoring.RdFrequency scoring
frequencyScoring(sequence.list, frequency.mat)A vector list of sequences
A matrix output from `createFrequencyMat`
A vector of frequency score
data('phospho_L6_ratio_pe')
data('KinaseMotifs')
# Extracting first 10 sequences for demonstration purpose
seqs = Sequence(phospho.L6.ratio.pe)
seqs = seqs[seq(10)]
# extracting flanking sequences
seqWin = mapply(function(x) {
mid <- (nchar(x)+1)/2
substr(x, start=(mid-7), stop=(mid+7))
}, seqs)
# The first 10 for demonstration purpose
phospho.L6.ratio = SummarizedExperiment::assay(phospho.L6.ratio.pe,
"Quantification")[seq(10),]
# minimum number of sequences used for compiling motif for each kinase.
numMotif=5
motif.mouse.list.filtered <-
motif.mouse.list[which(motif.mouse.list$NumInputSeq >= numMotif)]
# scoring all phosphosites against all motifs
motifScoreMatrix <-
matrix(NA, nrow=nrow(phospho.L6.ratio),
ncol=length(motif.mouse.list.filtered))
rownames(motifScoreMatrix) <- rownames(phospho.L6.ratio)
colnames(motifScoreMatrix) <- names(motif.mouse.list.filtered)
# Scoring phosphosites against kinase motifs
for(i in seq_len(length(motif.mouse.list.filtered))) {
motifScoreMatrix[,i] <-
frequencyScoring(seqWin, motif.mouse.list.filtered[[i]])
cat(paste(i, '.', sep=''))
}
#> 1.2.3.4.5.6.7.8.9.10.11.12.13.14.15.16.17.18.19.20.21.22.23.24.25.26.27.28.29.30.31.32.33.34.35.36.37.38.39.40.41.42.43.44.45.46.47.48.49.50.51.52.53.54.55.56.57.58.59.60.61.62.63.64.65.66.67.68.69.70.71.72.73.74.75.76.77.78.79.80.81.82.83.84.85.86.87.88.89.90.91.92.93.94.95.96.97.98.99.100.101.102.103.104.105.106.107.108.109.110.111.112.113.114.