## ----包括= false -----------------------------------------------------------------------------------------------------------------库（Knitr）opts_chunk $ set（tidy = false）## ----加载邮票，消息= false ----------------------------------------------------库（PEPDAT）库（Pepstat）## ------数据 - - - - - - - - - - - - - - - - - - - - - - - -------------------- mapfile <-system.file（“ extdata/mapping.csv”，package =“ pepdat”）dirtoparse <-system.file（“ extdata/gpr_samples”，package =“ pepdat”）pset < - makepeptideset（files = null，path = dirtoparse，mapper.file = mapfile，log = true）## ------------------------------------------ - - - - - - - - - - - - - - - - - - - - - - - - 读.csv（mapfile）## -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- pSetNoCtrl <- makePeptideSet(files = NULL, path = dirToParse, mapping.file = mapFile, log = TRUE, rm.control.list = c（“ jpt-control”，“ ig”，“ cy3”），empty.control.list = c（“空”，“空白控制”））## -------------------= true，图。PlotArayImage（PSET，ARRAY.INDEX = 1）## ----绘制堆放= true = true，fig.width = 7.48，图。Height= 3 --------------------------------------------------------------------------------plotArayResiduals（pset，array.index = 1，smooth = true）## ----创建pep-load-data ------------------------------------------------------------------------------------------------------------------------------------------- peps <- read.csv(system.file("extdata/pep_info.csv", package=“ pepdat”））头（PEPS）## ----创建DB ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- pep_custom <- create_db(peps) ## ----create-db-GR --------------------------------------------------------------------------------------- pep_custom <- create_db(pep_custom) ## ----summarizePeptideSet------------------------------------------------------ psSet <- summarizePeptides(pSet, summary = "mean", position = pep_custom) ## ----normalizeArray----------------------------------------------------------- pnSet <- normalizeArray(psSet) ## ----slidingMean-------------------------------------------------------------- psmSet <- slidingMean(pnSet, width = 9) ## ----slidingMean-splitbyclade------------------------------------------------- psmSetAg <- slidingMean(pnSet, width = 9, split.by.clade = FALSE) ## ----makeCalls---------------------------------------------------------------- calls <- makeCalls(psmSet, freq = TRUE, group = "treatment", cutoff = .1, method = "FDR", verbose = TRUE) ## ----makeCalls-aggregate------------------------------------------------------ callsAg <- makeCalls(psmSetAg, freq = TRUE, group = "treatment", cutoff = .1, method = "FDR") ## ----restab------------------------------------------------------------------- summary <- restab(psmSet, calls) head(summary) ## ----plot-inter, fig.height=4, message=FALSE---------------------------------- library(Pviz) summaryAg <- restab(psmSetAg, callsAg) plot_inter(summaryAg) ## ----plot-clade, fig.height=4------------------------------------------------- plot_clade(summary, clade=c("A", "M", "CRF01"), from = 300, to = 520) ## ----shinyApp, eval = FALSE--------------------------------------------------- # shinyPepStat() ## ----quick-analysis, results='hide', message=FALSE---------------------------- library(pepStat) library(pepDat) mapFile <- system.file("extdata/mapping.csv", package = "pepDat") dirToParse <- system.file("extdata/gpr_samples", package = "pepDat") ps <- makePeptideSet(files = NULL, path = dirToParse, mapping.file = mapFile) data(pep_hxb2) ps <- summarizePeptides(ps, summary = "mean", position = pep_hxb2) ps <- normalizeArray(ps) ps <- slidingMean(ps) calls <- makeCalls(ps, group = "treatment") summary <- restab(ps, calls) ## ----sessionInfo-------------------------------------------------------------- sessionInfo()