## ----setup, echo=FALSE, results="hide"---------------------------------------- knitr::opts_chunk$set(tidy = FALSE, cache = FALSE, dev = "png", message = FALSE, error = FALSE, warning = TRUE) ## ----libs--------------------------------------------------------------------- library(qPLEXanalyzer) library(gridExtra) data(human_anno) data(exp2_Xlink) ## ----Import------------------------------------------------------------------- MSnset_data <- convertToMSnset(exp2_Xlink$intensities, metadata = exp2_Xlink$metadata, indExpData = c(7:16), Sequences = 2, Accessions = 6) exprs(MSnset_data) <- exprs(MSnset_data)+1.1 MSnset_data ## ----Filter, fig.width=6, fig.height=5, fig.cap="Figure 1: Density plots of raw intensities for TMT-10plex experiment."---- intensityPlot(MSnset_data, title = "Peptide intensity distribution") ## ----boxplot, fig.width=6, fig.height=5, fig.cap="Figure 2: Boxplot of raw intensities for TMT-10plex experiment."---- intensityBoxplot(MSnset_data, title = "Peptide intensity distribution") ## ----rliplot, fig.width=6, fig.height=5, fig.cap="Figure 3: RLI of raw intensities for TMT-10plex experiment."---- rliPlot(MSnset_data, title = "Relative Peptide intensity") ## ----Corrplot, fig.width=6, fig.height=6, fig.cap="Figure 4: Correlation plot of peptide intensities"---- corrPlot(MSnset_data) ## ----hierarchicalplot, fig.width=6, fig.height=5, fig.cap="Figure 5: Clustering plot of peptide intensitites"---- exprs(MSnset_data) <- exprs(MSnset_data) + 0.01 hierarchicalPlot(MSnset_data) ## ----pcaplot, fig.width=6, fig.height=5, fig.cap="Figure 6: PCA plot of peptide intensitites"---- pcaPlot(MSnset_data, labelColumn = "BioRep", pointsize = 3) ## ----coverageplot, fig.width=6, fig.height=1.5, fig.cap="Figure 7: Peptide sequence coverage plot"---- mySequenceFile <- system.file("extdata", "P03372.fasta", package = "qPLEXanalyzer") coveragePlot(MSnset_data, ProteinID = "P03372", ProteinName = "ESR1", fastaFile = mySequenceFile) ## ----norm, fig.width=7, fig.height=7, fig.cap="Figure 8: Peptide intensity distribution with various normalization methods"---- 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 = "Within Group Scaling") grid.arrange(p1, p2, p3, p4, ncol = 2, nrow = 2) ## ----annotation, 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) %>% # arrange(Accessions) # head(first_ten_anno) ## ----annotationReal, echo=FALSE----------------------------------------------- library(dplyr) proteins <- unique(fData(MSnset_data)$Accessions)[1:10] filter(human_anno, Accessions%in%proteins) %>% as_tibble() %>% arrange(Accessions) %>% head() ## ----summarize---------------------------------------------------------------- MSnset_Pnorm <- summarizeIntensities(MSnset_norm_gs, summarizationFunction = sum, annotation = human_anno) ## ----pepIntensity, fig.width=6, fig.height=5, fig.cap="Figure 9: Summarized protein intensity"---- peptideIntensityPlot(MSnset_data, combinedIntensities = MSnset_Pnorm, ProteinID = "P03372", ProteinName = "ESR1") ## ----regress, fig.width=6, fig.height=4, fig.cap="Figure 10: Correlation between bait protein and enriched proteins before and after regression"---- data(exp3_OHT_ESR1) MSnset_reg <- convertToMSnset(exp3_OHT_ESR1$intensities_qPLEX2, metadata = exp3_OHT_ESR1$metadata_qPLEX2, indExpData = c(7:16), Sequences = 2, Accessions = 6) MSnset_P <- summarizeIntensities(MSnset_reg, summarizationFunction = sum, annotation = human_anno) MSnset_P <- rowScaling(MSnset_P, scalingFunction = mean) IgG_ind <- which(pData(MSnset_P)$SampleGroup == "IgG") Reg_data <- regressIntensity(MSnset_P, controlInd = IgG_ind, ProteinId = "P03372") ## ----diffexp------------------------------------------------------------------ contrasts <- c(DSG.FA_vs_FA = "DSG.FA - FA") diffstats <- computeDiffStats(MSnset_Pnorm, contrasts = contrasts) diffexp <- getContrastResults(diffstats, contrast = contrasts, controlGroup = "IgG") ## ----MAplot, fig.width=6,fig.height=4, fig.cap="Figure 11: MA plot of the quantified proteins"---- maVolPlot(diffstats, contrast = contrasts, plotType = "MA", title = contrasts) ## ----volcano, fig.width=6, fig.height=4, fig.cap="Figure 12: Volcano plot of the quantified proteins"---- maVolPlot(diffstats, contrast = contrasts, plotType = "Volcano", title = contrasts) ## ----info,echo=TRUE----------------------------------------------------------- sessionInfo()