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.Rhistory
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setwd('/Users/Meena/Dropbox/MSstats_GitHub_private/MSstats/vignettes')
getwd()
library('MSstats', warn.conflicts = F, quietly = T, verbose = F)
DDA2009.superhirn<-read.csv("RawData.DDA.csv")
head(DDA2009.superhirn)
DDA2009.TMP <- dataProcess(raw = DDA2009.superhirn, fillIncompleteRows = TRUE,
normalization = 'equalizeMedians',
summaryMethod = 'TMP',
censoredInt="NA", cutoffCensored="minFeatureNRun",
MBimpute=TRUE)
names(DDA2009.TMP)
# the data after reformatting and normalization
head(DDA2009.TMP$ProcessedData)
# run-level summarized data
head(DDA2009.TMP$RunlevelData)
# Since this is not model-based, no model summary (here DDAskyline.quant$ModelQC=NULL).
# Only with 'summaryMethod="linear"'
head(DDA2009.TMP$ModelQC)
# here 'TMP'
head(DDA2009.TMP$SummaryMethod)
# predict values by AFT with 'MBimpute=TRUE'.
# These values are matching with rownames of DDA2009.TMP$ProcessedData
head(DDA2009.TMP$PredictBySurvival)
DDA2009.TMP.random <- dataProcess(raw = DDA2009.superhirn, fillIncompleteRows = TRUE,
normalization = 'equalizeMedians',
summaryMethod = 'TMP',
censoredInt=NULL)
DDA2009.linear <- dataProcess(raw = DDA2009.superhirn,
summaryMethod="linear", censoredInt=NULL)
# accerated failure model with left-censored. NA intensities are assumed as censored
DDA2009.linear.censored <- dataProcess(raw = DDA2009.superhirn,
summaryMethod="linear", censoredInt="NA")
dataProcessPlots(data = DDA2009.TMP, type="QCplot", ylimUp=35)
dataProcessPlots(data = DDA2009.TMP, type="QCplot", ylimUp=35,
which.Protein="yeast", address="yeast_eqmedians_")
dataProcessPlots(data = DDA2009.TMP, type="Profileplot", ylimUp=35,
featureName="NA", width=7, height=7, address="DDA2009_TMP_")
dataProcessPlots(data = DDA2009.TMP.random, type="Profileplot", ylimUp=35,
featureName="NA", width=7, height=7,
originalPlot=FALSE, summaryPlot=TRUE, address="DDA2009_TMP_random_")
comparison1<-matrix(c(-1,1,0,0,0,0),nrow=1)
comparison2<-matrix(c(0,-1,1,0,0,0),nrow=1)
comparison3<-matrix(c(0,0,-1,1,0,0),nrow=1)
comparison4<-matrix(c(0,0,0,-1,1,0),nrow=1)
comparison5<-matrix(c(0,0,0,0,-1,1),nrow=1)
comparison6<-matrix(c(1,0,0,0,0,-1),nrow=1)
comparison<-rbind(comparison1,comparison2,comparison3,comparison4,comparison5,comparison6)
row.names(comparison)<-c("C2-C1","C3-C2","C4-C3","C5-C4","C6-C5","C1-C6")
DDA2009.comparisons <- groupComparison(contrast.matrix = comparison, data=DDA2009.TMP)
names(DDA2009.comparisons)
names(DDA2009.comparisons$ComparisonResult)
SignificantProteins =
DDA2009.comparisons$ComparisonResult[DDA2009.comparisons$ComparisonResult$adj.pvalue < 0.05 ,]
nrow(SignificantProteins)
install.packages("rmarkdown")
install.packages("rmarkdown")
setwd("/Users/Meena/Dropbox/MSstats_GitHub_document")
raw <- read.csv(file = "ControlMixerMSstatsInputfromskyline.csv")
head(raw)
DDARawData.Skyline<-raw
rm("raw")
save(DDARawData.Skyline, file="DDARawData.Skyline.RData")
rm(list=ls())
library(MSstats)
browseVignettes("MSstats")
?MSstats