## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width=8, fig.height=8 ) ## ---- message=FALSE, warning=FALSE-------------------------------------------- library(MSstatsTMTPTM) library(MSstatsTMT) library(MSstats) library(dplyr) ## ---- eval = FALSE------------------------------------------------------------ # if (!requireNamespace("BiocManager", quietly = TRUE)) # install.packages("BiocManager") # # BiocManager::install("MSstatsTMTPTM") ## ----------------------------------------------------------------------------- # read in raw data files # raw.ptm <- read.csv(file="raw.ptm.csv", header=TRUE) head(raw.ptm) ## ----------------------------------------------------------------------------- head(raw.protein) # raw.protein <- read.csv(file="raw.protein.csv", header=TRUE) ## ---- results='hide', message=FALSE, warning=FALSE---------------------------- # Use proteinSummarization function from MSstatsTMT to summarize raw data quant.msstats.ptm <- proteinSummarization(raw.ptm, method = "msstats", global_norm = TRUE, reference_norm = FALSE, MBimpute = TRUE) quant.msstats.protein <- proteinSummarization(raw.protein, method = "msstats", global_norm = TRUE, reference_norm = FALSE, MBimpute = TRUE) ## ----------------------------------------------------------------------------- head(quant.msstats.ptm) head(quant.msstats.protein) ## ---- results='hide', message=FALSE, warning=FALSE---------------------------- # test for all the possible pairs of conditions model.results.pairwise <- groupComparisonTMTPTM(data.ptm=quant.msstats.ptm, data.protein=quant.msstats.protein) ## ---- message=FALSE, warning=FALSE------------------------------------------- # Specify comparisons comparison<-matrix(c(1,0,0,-1,0,0, 0,1,0,0,-1,0, 0,0,-1,0,0,-1, 1,0,-1,0,0,0, 0,1,-1,0,0,0, 0,0,0,1,0,-1, 0,0,0,0,1,-1, .25,.25,-.5,.25,.25,-.5, 1/3,1/3,1/3,-1/3,-1/3,-1/3),nrow=9, ncol=6, byrow=TRUE) # Set the names of each row row.names(comparison)<-c('1-4', '2-5', '3-6', '1-3', '2-3', '4-6', '5-6', 'Partial', 'Third') # Set the column names colnames(comparison)<- c('Condition_1', 'Condition_2', 'Condition_3', 'Condition_4', 'Condition_5', 'Condition_6') comparison ## ---- results='hide', message=FALSE, warning=FALSE---------------------------- # test for specified condition comparisons only model.results.contrast <- groupComparisonTMTPTM(data.ptm=quant.msstats.ptm, data.protein=quant.msstats.protein, contrast.matrix = comparison) ## ----------------------------------------------------------------------------- names(model.results.contrast) ptm_model <- model.results.contrast[[1]] protein_model <- model.results.contrast[[2]] adjusted_model <- model.results.contrast[[3]] head(adjusted_model) ## ----------------------------------------------------------------------------- groupComparisonPlots(data = adjusted_model, type = 'VolcanoPlot', ProteinName = FALSE, which.Comparison = '1-4', address = FALSE) ## ----------------------------------------------------------------------------- dataProcessPlotsTMTPTM(data.ptm = raw.ptm, data.protein = raw.protein, data.ptm.summarization = quant.msstats.ptm, data.protein.summarization = quant.msstats.protein, type = 'ProfilePlot', which.Protein = 'Protein_2391_Y40', address = FALSE) ## ----------------------------------------------------------------------------- dataProcessPlotsTMTPTM(data.ptm = raw.ptm %>% filter( Condition %in% c('Condition_1', 'Condition_4')), data.protein = raw.protein %>% filter( Condition %in% c('Condition_1', 'Condition_4')), data.ptm.summarization = quant.msstats.ptm %>% filter( Condition %in% c('Condition_1', 'Condition_4')), data.protein.summarization = quant.msstats.protein %>% filter(Condition %in% c( 'Condition_1', 'Condition_4')), type = 'ProfilePlot', which.Protein = 'Protein_2391_Y40', originalPlot = FALSE, address = FALSE) model_df <- rbind(adjusted_model %>% filter( Protein == 'Protein_2391_Y40' & Label == '1-4') %>% select(-Tvalue), ptm_model %>% filter( Protein == 'Protein_2391_Y40' & Label == '1-4' ) %>% select(-issue), protein_model %>% filter( Protein == 'Protein_2391' & Label == '1-4' ) %>% select(-issue)) model_df <- data.frame(model_df) rownames(model_df) <- c('Adjusted PTM', 'PTM', 'Protein') model_df ## ----------------------------------------------------------------------------- dataProcessPlotsTMTPTM(data.ptm = raw.ptm %>% filter( Condition %in% c('Condition_2', 'Condition_5')), data.protein = raw.protein %>% filter( Condition %in% c('Condition_2', 'Condition_5')), data.ptm.summarization = quant.msstats.ptm %>% filter(Condition %in% c('Condition_2', 'Condition_5')), data.protein.summarization = quant.msstats.protein %>% filter(Condition %in% c('Condition_2', 'Condition_5')), type = 'ProfilePlot', which.Protein = 'Protein_1076_Y67', originalPlot = FALSE, address = FALSE) model_df <- rbind(adjusted_model %>% filter( Protein == 'Protein_1076_Y67' & Label == '2-5') %>% select(-Tvalue), ptm_model %>% filter( Protein == 'Protein_1076_Y67' & Label == '2-5' ) %>% select(-issue), protein_model %>% filter( Protein == 'Protein_1076' & Label == '2-5' ) %>% select(-issue)) model_df <- data.frame(model_df) rownames(model_df) <- c('Adjusted PTM', 'PTM', 'Protein') model_df ## ----session------------------------------------------------------------------ sessionInfo()