## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(echo = TRUE) ## ----eval=TRUE---------------------------------------------------------------- #Load the library library(phosphonormalizer) #Enriched data overview head(enriched.rd) #Non-enriched data overview head(non.enriched.rd) ## ----eval=FALSE--------------------------------------------------------------- # ## try http:// if https:// URLs are not supported # if (!requireNamespace("BiocManager", quietly=TRUE)) # install.packages("BiocManager") # BiocManager::install("phosphonormalizer") ## ----eval=TRUE, fig.height = 4, fig.width = 6, fig.align = "center"----------- #Load the library library(phosphonormalizer) #Specify the column numbers of abundances in the original data.frame, #from both enriched and non-enriched runs samplesCols <- data.frame(enriched=3:17, non.enriched=3:17) #Specify the column numbers of sequence and modification in the original data.frame, #from both enriched and non-enriched runs modseqCols <- data.frame(enriched = 1:2, non.enriched = 1:2) #The samples and their technical replicates techRep <- factor(x = c(1,1,1,2,2,2,3,3,3,4,4,4,5,5,5)) #If the paramter plot.fc set, the corresponding plots of Sample fold changes is produced #Here, for demonstration, the fold change distributions are shown for samples 3 vs 1 plot.param <- list(control = c(1), samples = c(3)) #Call the function norm <- normalizePhospho(enriched = enriched.rd, non.enriched = non.enriched.rd, samplesCols = samplesCols, modseqCols = modseqCols, techRep = techRep, plot.fc = plot.param)