## ----options,echo=FALSE----------------------------------------------- options(width=72) ## ----libs, message=FALSE, cache=TRUE, warning= FALSE------------------ library(qPLEXanalyzer) library(gridExtra) data(human_anno) data(exp2_Xlink) ## ----Import,fig.width=6,fig.height=5,out.width='.85\\textwidth',message=FALSE,cache=TRUE---- MSnset_data <- convertToMSnset(exp2_Xlink$intensities, metadata = exp2_Xlink$metadata, indExpData = c(7:16), Sequences = 2, Accessions = 6 ) ## ----Filter,fig.width=6,fig.height=5,out.width='.85\\textwidth', fig.cap="Density plots of raw intensities for TMT-10plex experiment.", message=FALSE,cache=TRUE,fig.asp=0.7---- intensityPlot(MSnset_data, title = "Peptide intensity distribution") ## ----boxplot,fig.width=6,fig.height=5,out.width='.85\\textwidth', fig.cap="Boxplot of raw intensities for TMT-10plex experiment.", message=FALSE,cache=TRUE,fig.asp=0.7---- intensityBoxplot(MSnset_data, title = "Peptide intensity distribution") ## ----rliplot,fig.width=6,fig.height=5,out.width='.85\\textwidth', fig.cap="RLI of raw intensities for TMT-10plex experiment.", message=FALSE,cache=TRUE,fig.asp=0.7---- rliPlot(MSnset_data, title = "Relative Peptide intensity") ## ----Corrplot,fig.width=7,fig.height=7,out.width='.85\\textwidth', fig.cap="Correlation plot of peptide intensitites", message=FALSE,cache=TRUE---- corrPlot(MSnset_data) ## ----hierarchicalplot,fig.width=7.1,fig.height=5,out.width='0.85\\textwidth', fig.cap="Clustering plot of peptide intensitites", message=FALSE,cache=TRUE,fig.asp=0.8---- exprs(MSnset_data) <- exprs(MSnset_data) + 0.01 hierarchicalPlot(MSnset_data) ## ----pcaplot,fig.width=6,fig.height=5,out.width='.85\\textwidth', fig.cap="PCA plot of peptide intensitites", message=FALSE,cache=TRUE,fig.asp=0.7---- pcaPlot(MSnset_data, labelColumn = "BioRep", pointsize = 2) ## ----coverageplot, fig.width=6, fig.height=1.5, out.width='.85\\textwidth', fig.cap="Peptide sequence coverage plot", message=FALSE, cache=TRUE---- mySequenceFile <- system.file("extdata", "P03372.fasta", package = "qPLEXanalyzer") coveragePlot(MSnset_data, ProteinID = "P03372", ProteinName = "ESR1", fastaFile = mySequenceFile ) ## ----norm,fig.width=10,fig.height=9,out.width='.85\\textwidth', fig.cap="Peptide intensity distribution with various normalization methods", message=FALSE,cache=TRUE---- MSnset_data <- MSnset_data[, -5] p1 <- intensityPlot(MSnset_data, title = "No normalization") MSnset_norm_q <- normalizeQuantiles(MSnset_data) p2 <- intensityPlot(MSnset_norm_q, title = "Quantile") MSnset_norm_ns <- normalizeScaling(MSnset_data, scalingFunction = median) p3 <- intensityPlot(MSnset_norm_ns, title = "Scaling") MSnset_norm_gs <- groupScaling(MSnset_data, scalingFunction = median, groupingColumn = "SampleGroup") p4 <- intensityPlot(MSnset_norm_gs, title = "WithinGrp Scaling") grid.arrange(p1, p2, p3, p4, ncol = 2, nrow = 2) ## ----annotation,out.width='.85\\textwidth',eval=FALSE----------------- # library(UniProt.ws) # library(dplyr) # proteins <- unique(fData(MSnset_data)$Accessions)[1:10] # columns <- c("ENTRY-NAME", "PROTEIN-NAMES", "GENES") # hs <- UniProt.ws::UniProt.ws(taxId = 9606) # first_ten_anno <- UniProt.ws::select(hs, proteins, columns, "UNIPROTKB") %>% # as_tibble() %>% # mutate(GeneSymbol = gsub(" .*", "", GENES)) %>% # select( # Accessions = "UNIPROTKB", Gene = "ENTRY-NAME", # Description = "PROTEIN-NAMES", GeneSymbol # ) # head(arrange(first_ten_anno, Accessions)) ## ----annotationReal,out.width='.85\\textwidth',message=FALSE,cache=TRUE,echo=FALSE---- library(dplyr) proteins <- unique(fData(MSnset_data)$Accessions)[1:10] filter(human_anno, Accessions%in%proteins) %>% tbl_df() %>% arrange(Accessions) %>% head() ## ----summarize,fig.width=6,fig.height=5,out.width='.85\\textwidth',message=FALSE,cache=TRUE---- MSnset_Pnorm <- summarizeIntensities(MSnset_norm_gs, sum, human_anno) ## ----pepIntensity,fig.width=6,fig.height=5,out.width='.85\\textwidth', fig.cap="Summarized protein intensity", message=FALSE,cache=TRUE---- peptideIntensityPlot(MSnset_data, combinedIntensities = MSnset_Pnorm, ProteinID = "P03372", ProteinName = "ESR1" ) ## ----regress,fig.width=6,fig.height=5,out.width='.85\\textwidth', fig.cap="Correlation between bait protein and enriched proteins before and after regression", message=FALSE,cache=TRUE,fig.asp=0.7---- data(exp3_OHT_ESR1) MSnset_reg <- convertToMSnset(exp3_OHT_ESR1$intensities_qPLEX2, metadata = exp3_OHT_ESR1$metadata_qPLEX2, indExpData = c(7:16), Sequences = 2, Accessions = 6 ) MSnset_P <- summarizeIntensities(MSnset_reg, sum, human_anno) MSnset_P <- rowScaling(MSnset_P, mean) IgG_ind <- which(pData(MSnset_P)$SampleGroup == "IgG") Reg_data <- regressIntensity(MSnset_P, controlInd = IgG_ind, ProteinId = "P03372") ## ----diffexp,fig.width=5,fig.height=4,out.width='.85\\textwidth', fig.cap="MA plot of the quantified proteins", message=FALSE,cache=TRUE,fig.asp=0.65---- contrasts <- c(DSG.FA_vs_FA = "DSG.FA - FA") diffstats <- computeDiffStats(MSnset_Pnorm, contrasts = contrasts) diffexp <- getContrastResults( diffstats = diffstats, contrast = contrasts, controlGroup = "IgG" ) maVolPlot(diffstats, contrast = contrasts, plotType = "MA", title = contrasts) ## ----volcano,fig.width=5,fig.height=4,out.width='.85\\textwidth', fig.cap="Volcano plot of the quantified proteins", message=FALSE,cache=TRUE,fig.asp=0.65---- maVolPlot(diffstats, contrast = contrasts, plotType = "Volcano", title = contrasts) ## ----info,echo=TRUE--------------------------------------------------- sessionInfo()