## ----style, eval=TRUE, echo=FALSE, results="asis"------------------------
BiocStyle::latex()


## ----environment, cache=FALSE, echo=FALSE--------------------------------
suppressPackageStartupMessages(library("ggplot2"))
suppressPackageStartupMessages(library("MSnbase"))
suppressPackageStartupMessages(library("zoo"))
suppressPackageStartupMessages(require("Rdisop"))
suppressPackageStartupMessages(require("pRolocdata"))
suppressPackageStartupMessages(require("pRoloc"))
library("grid")
library("reshape2")


## ----readdata, echo=TRUE, cache=FALSE, tidy=FALSE------------------------
file <- dir(system.file(package = "MSnbase", dir = "extdata"),
            full.names = TRUE, pattern = "mzXML$")
rawdata <- readMSData(file, msLevel = 2, verbose = FALSE)


## ----MSnExp, cache=FALSE, echo=TRUE--------------------------------------
library("MSnbase")
itraqdata
head(fData(itraqdata))


## ----experimentsize, echo=FALSE, cache=FALSE-----------------------------
sz <- sum(sapply(assayData(itraqdata), object.size)) +
  object.size(itraqdata)
sz <- as.numeric(sz)
sz <- round(sz/(1024^2), 2)


## ----Spectrum, cache=FALSE, echo=TRUE------------------------------------
sp <- itraqdata[["X1"]]
sp


## ----accessors, cache=FALSE, echo=TRUE-----------------------------------
peaksCount(sp)
head(peaksCount(itraqdata))
rtime(sp)
head(rtime(itraqdata))


## ----ReporterIons--------------------------------------------------------
iTRAQ4
TMT10


## ----msmap, eval=FALSE---------------------------------------------------
## ## downloads the data
## library("rpx")
## px1 <- PXDataset("PXD000001")
## mzf <- pxget(px1, 6)
## 
## ## reads the data
## ms <- openMSfile(mzf)
## hd <- header(ms)
## 
## ## a set of spectra of interest: MS1 spectra eluted
## ## between 30 and 35 minutes retention time
## ms1 <- which(hd$msLevel == 1)
## rtsel <- hd$retentionTime[ms1] / 60 > 30 &
##     hd$retentionTime[ms1] / 60 < 35
## 
## ## the map
## M <- MSmap(ms, ms1[rtsel], 521, 523, .005, hd, zeroAsNA = TRUE)


## ----msmaplaod, echo=FALSE-----------------------------------------------
mrda <- dir(system.file(package = "MSnbase", dir = "extdata"),
            full.names = TRUE, pattern = "M.rda$")
mrda2 <- dir(system.file(package = "MSnbase", dir = "extdata"),
            full.names = TRUE, pattern = "M2.rda$")
load(mrda)
load(mrda2)


## ----msmaphow------------------------------------------------------------
M


## ----mapheat, dev='pdf', fig.width=5, fig.height=5-----------------------
plot(M, aspect = 1, allTicks = FALSE)


## ----map3d1, dev='pdf', fig.width=4, fig.height=4------------------------
plot3D(M)


## ----msmap2, eval=FALSE--------------------------------------------------
## i <- ms1[which(rtsel)][1]
## j <- ms1[which(rtsel)][2]
## M2 <- MSmap(ms, i:j, 100, 1000, 1, hd)


## ----m2------------------------------------------------------------------
M2


## ----map3d2, dev='pdf', fig.width=4, fig.height=4------------------------
plot3D(M2)


## ----spectrumPlot, dev='pdf', fig.width=6, fig.height=4, fig.keep='high'----
plot(sp, reporters = iTRAQ4, full = TRUE)


## ----bsaSelect, eval=TRUE, echo=FALSE------------------------------------
## bsasel <- fData(itraqdata)$ProteinAccession == "BSA"
bsasel <- 1:3


## ----subset, echo=TRUE---------------------------------------------------
sel <- fData(itraqdata)$ProteinAccession == "BSA"
bsa <- itraqdata[sel]
bsa
as.character(fData(bsa)$ProteinAccession)


## ----msnexpPlot, dev='pdf', fig.width=3.7, fig.height=4.5, fig.keep='last'----
plot(bsa, reporters = iTRAQ4, full = FALSE) + theme_gray(8)


## ----msnexpIdentification, echo=TRUE, cache=FALSE, tidy=FALSE------------
## find path to a mzXML file
quantFile <- dir(system.file(package = "MSnbase", dir = "extdata"),
                 full.name = TRUE, pattern = "mzXML$")
## find path to a mzIdentML file
identFile <- dir(system.file(package = "MSnbase", dir = "extdata"),
                 full.name = TRUE, pattern = "dummyiTRAQ.mzid")
## create basic MSnExp
msexp <- readMSData(quantFile, verbose = FALSE)
head(fData(msexp), n = 2)


## ----msnexpIdentification2, echo=TRUE, cache=FALSE, tidy=FALSE-----------
## add identification information
msexp <- addIdentificationData(msexp, id = identFile,
                               verbose = FALSE)
head(fData(msexp), n = 2)


## ----msnexpIdentification3, echo=TRUE, cache=FALSE, tidy=FALSE-----------
idSummary(msexp)


## ----fragplot------------------------------------------------------------
itraqdata2 <- pickPeaks(itraqdata, verbose=FALSE)
i <- 14
s <- as.character(fData(itraqdata2)[i, "PeptideSequence"])


## ----fragplotfig, dev='pdf', fig.width=5, fig.height=5-------------------
plot(itraqdata2[[i]], s, main = s)


## ----msnexpIdentification4, echo=TRUE, cache=FALSE, tidy=FALSE-----------
fData(msexp)$pepseq
msexp <- removeNoId(msexp)
fData(msexp)$pepseq
idSummary(msexp)


## ----calculateFragments, echo=TRUE, cache=FALSE, tidy=FALSE--------------
calculateFragments("ACEK",
                   type=c("a", "b", "c", "x", "y", "z"))


## ----msnexpcalculateFragments, echo=TRUE, cache=FALSE, tidy=FALSE--------
pepseq <- fData(msexp)$pepseq[1]
calculateFragments(pepseq, msexp[[1]], type=c("b", "y"))


## ----removePeaks, echo=TRUE, cache=FALSE---------------------------------
experiment <- removePeaks(itraqdata, t = 400, verbose = FALSE)
## total ion current
ionCount(itraqdata[["X55"]])
ionCount(experiment[["X55"]])


## ----spectrum-clean-plot, dev='pdf', fig.width=6, fig.height=3, echo=FALSE, fig.keep='high'----
p1 <- plot(itraqdata[["X55"]], full = TRUE, plot = FALSE) + theme_gray(5)
p2 <- plot(experiment[["X55"]], full = TRUE, plot = FALSE) + theme_gray(5)
grid.newpage()
pushViewport(viewport(layout = grid.layout(1, 2)))
vplayout <- function(x, y)
  viewport(layout.pos.row = x, layout.pos.col = y)
print(p1,vp=vplayout(1,1))
print(p2,vp=vplayout(1,2))


## ----clean, echo=TRUE, cache=FALSE---------------------------------------
## number of peaks
peaksCount(itraqdata[["X55"]])
peaksCount(experiment[["X55"]])
experiment <- clean(experiment, verbose = FALSE)
peaksCount(experiment[["X55"]])


## ----preprosp, cache=FALSE, echo=FALSE-----------------------------------
int <- c(0,1,1,3,1,1,0,0,0,1,3,7,3,1,0)
mz <- c(113.9,114.0,114.05,114.1,114.15,114.2,114.25,
        114.3,114.35,114.4,114.42,114.48,114.5,114.55,114.6)
ppsp <- new("Spectrum2",intensity=int,mz=mz,centroided=FALSE)
p1 <- plot(ppsp, full = TRUE, plot = FALSE) + theme_gray(5) +
  geom_point(size=3,alpha=I(1/3)) +
  geom_hline(yintercept=3,linetype=2) +
  ggtitle("Original spectrum")
p2 <- plot(removePeaks(ppsp,t=3), full=TRUE, plot = FALSE) +
  theme_gray(5) +
  geom_point(size=3,alpha=I(1/3)) +
  geom_hline(yintercept=3,linetype=2) +
  ggtitle("Peaks < 3 removed")
p3 <- plot(clean(removePeaks(ppsp,t=3)), full = TRUE, plot = FALSE) +
  theme_gray(5) +
  geom_point(size=3,alpha=I(1/3)) +
  geom_hline(yintercept=3,linetype=2) +
  ggtitle("Peaks < 3 removed and cleaned")


## ----preprocPlot, dev='pdf', fig.width=3, fig.height=6, echo=FALSE-------
grid.newpage()
pushViewport(viewport(layout = grid.layout(3, 1)))
print(p1, vp=vplayout(1,1))
print(p2, vp=vplayout(2,1))
print(p3, vp=vplayout(3,1))


## ----trimMz, echo=TRUE, cache=FALSE--------------------------------------
range(mz(itraqdata[["X55"]]))
experiment <- trimMz(experiment, mzlim = c(112,120))
range(mz(experiment[["X55"]]))
experiment


## ----reporters, echo=TRUE, cache=FALSE-----------------------------------
mz(iTRAQ4)
width(iTRAQ4)


## ----simplesp, cache=FALSE, echo=FALSE, fig.keep='none'------------------
int <- c(0,1,1,3,1,1,0)
mz <- c(113.9,114.0,114.05,114.1,114.15,114.2,114.25)
ssp <- new("Spectrum2",intensity=int,mz=mz,centroided=FALSE)
p <- plot(ssp, full=TRUE, plot=FALSE)
p <- p + theme_gray(5)


## ----quantitationPlot, dev='pdf',fig.width=5, fig.height=5, echo=FALSE----
grid.newpage()
pushViewport(viewport(layout = grid.layout(2, 2)))
vplayout <- function(x, y)
  viewport(layout.pos.row = x, layout.pos.col = y)
print(p + ggtitle("Quantitation using 'sum'") +
      geom_point(size = 3, alpha = I(1/3), colour = "red"),
      vp = vplayout(1, 1))
print(p + ggtitle("Quantitation using 'max'") +
      geom_point(aes(x = 114.1, y = 3),
                 alpha = I(1/18),
                 colour = "red", size = 3),
      vp = vplayout(1, 2))
print(p +
      ggtitle("Trapezoidation and strict=FALSE") +
      geom_polygon(alpha = I(1/5), fill = "red"),
      vp = vplayout(2, 1))
print(p +
      ggtitle("Trapezoidation and strict=TRUE") +
      geom_polygon(aes(x = c(NA, 114.05, 114.05, 114.1, 114.15, 114.15, NA),
                       y=c(NA, 0, 1, 3, 1, 0, NA)), fill = "red", alpha = I(1/5)),
      vp = vplayout(2,2))


## ----quantify, echo=TRUE, cache=FALSE, tidy=FALSE------------------------
qnt <- quantify(experiment,
                method = "trap",
                reporters = iTRAQ4,
                strict = FALSE,
                verbose = FALSE)
qnt
head(exprs(qnt))


## ----filterNA, echo=TRUE-------------------------------------------------
table(is.na(qnt))
qnt <- filterNA(qnt, pNA = 0)
sum(is.na(qnt))


## ----removeNa, echo=TRUE, eval=FALSE-------------------------------------
## whichRow <- which(is.na((qnt))) %% nrow(qnt)
## qnt <- qnt[-whichRow, ]


## ----pheplus1, echo=TRUE, cache=FALSE------------------------------------
library(Rdisop)
## Phenylalanine immonium ion
Fim <- getMolecule("C8H10N")
getMass(Fim)
isotopes <- getIsotope(Fim)
F1 <- isotopes[2, 2]
F1


## ----purityCorrect, echo=TRUE, cache=FALSE, tidy = FALSE-----------------
impurities <- matrix(c(0.929, 0.059, 0.002, 0.000,
                       0.020, 0.923, 0.056, 0.001,
                       0.000, 0.030, 0.924, 0.045,
                       0.000, 0.001, 0.040, 0.923),
                     nrow = 4)
qnt.crct <- purityCorrect(qnt, impurities)
head(exprs(qnt))
head(exprs(qnt.crct))


## ----impute--------------------------------------------------------------
## an example MSnSet containing missing values
data(naset)
table(is.na(naset))
## number of NAs per protein
table(fData(naset)$nNA) 
x <- impute(naset, "min")
processingData(x)
table(is.na(x))


## ----miximpfig, echo=FALSE, dev='pdf', fig.width=8, fig.width=8----------
x <- impute(naset, "zero")
exprs(x)[exprs(x) != 0] <- 1

suppressPackageStartupMessages(library("gplots"))

heatmap.2(exprs(x), col = c("lightgray", "black"),
            scale = "none", dendrogram = "none",
            trace = "none", keysize = 0.5, key = FALSE,
            RowSideColors = ifelse(fData(x)$randna, "orange", "brown"),
            ColSideColors = rep(c("steelblue", "darkolivegreen"), each = 8))


## ----miximp--------------------------------------------------------------
x <- impute(naset, method = "mixed",
            randna = fData(naset)$randna,
            mar = "knn", mnar = "min")
x


## ----normalise, echo=TRUE, cache=FALSE-----------------------------------
qnt.max <- normalise(qnt, "max")
qnt.sum <- normalise(qnt, "sum")
qnt.quant <- normalise(qnt, "quantiles")
qnt.qrob <- normalise(qnt, "quantiles.robust")
qnt.vsn <- normalise(qnt, "vsn")


## ----normPlot, dev='pdf', fig.width=5, fig.height=7, echo=FALSE----------
.plot <- function(x,ttl=NULL) {
  boxplot(exprs(x),
          main=ifelse(is.null(ttl),processingData(x)@processing[2],ttl),
          cex.main=.8,
          cex.lab=.5,
          cex.axis=.5,
          cex=.8)
  grid()
}
oldmar <- par()$mar
par(mfrow=c(3,2),mar=c(2.9,2.9,2.9,1))
.plot(qnt, ttl = "Non-normalised data")
.plot(qnt.max, ttl = "Maximum")
.plot(qnt.sum, ttl = "Sum")
.plot(qnt.quant, ttl = "Quantile")
.plot(qnt.qrob, ttl = "Robust quantile")
.plot(qnt.vsn, ttl = "vsn")


## ----cvdata, echo=FALSE, cache=FALSE-------------------------------------
sd1 <- apply(log2(exprs(qnt))+10,1,sd)
mn1 <- apply(log2(exprs(qnt))+10,1,mean)
cv1 <- sd1/mn1
sd2 <- apply(exprs(qnt.vsn)+10,1,sd)
mn2 <- apply(exprs(qnt.vsn)+10,1,mean)
cv2 <- sd2/mn2
dfr <- rbind(data.frame(rank=order(mn1),cv=cv1,norm="raw"),
             data.frame(rank=order(mn2),cv=cv2,norm="vsn"))
library("zoo")
## rmed1 <- rollapply(cv1,7,function(x) median(x,na.rm=TRUE))
## rmed2 <- rollapply(cv2,7,function(x) median(x,na.rm=TRUE))
##
## Calling directly rollapply.zoo to make it zoo_1.6-4 compatible.
## The above requires zoo >= 1.7-0, which is as of 15 March 2011
## not yet available on CRAN (only on r-forge).
rmed1 <- zoo:::rollapply.zoo(cv1,7,function(x) median(x,na.rm=TRUE))
rmed2 <- zoo:::rollapply.zoo(cv2,7,function(x) median(x,na.rm=TRUE))
dfr2 <-
  rbind(data.frame(x=seq(1,70,by=(70/length(rmed1))),
                   y=rmed1,norm="raw"),
        data.frame(x=seq(1,70,by=(70/length(rmed1))),
                   y=rmed2,norm="vsn"))

p <- qplot(rank,cv,data=dfr,col=norm) +
  geom_line(data=dfr2,aes(x=x,y=y,colour=norm)) +
  theme_gray(7)


## ----cvPlot, dev='pdf', fig.width=5, fig.height=4, echo=FALSE------------
print(p)


## ----prepareMsnsetNormPlot, cache=FALSE, echo=FALSE, keep.fig='none'-----
p <- plot(normalise(experiment[bsasel], "max"),
          reporters = iTRAQ4, full = FALSE, plot = FALSE)
p <- p + theme_gray(7)


## ----msnexpNormPlot, dev='pdf', fig.width=5, fig.height=6, echo=FALSE----
print(p)


## ----makeGroups1,echo=FALSE,cache=FALSE----------------------------------
gb <- fData(qnt)$ProteinAccession


## ----makeGroups2,echo=TRUE,cache=FALSE-----------------------------------
gb <- fData(qnt)$ProteinAccession
table(gb)
length(unique(gb))


## ----combineFeatures, echo=TRUE, cache=FALSE-----------------------------
qnt2 <- combineFeatures(qnt, groupBy = gb, fun = "median")
qnt2


## ----count---------------------------------------------------------------
sc <- quantify(msexp, method = "count")
## lets modify out data for demonstration purposes
fData(sc)$accession[1] <- fData(sc)$accession[2]
fData(sc)$accession
sc <- combineFeatures(sc, groupBy = fData(sc)$accession,
                      fun = "sum")
exprs(sc)


## ----labelfree-----------------------------------------------------------
fData(msexp)[, c("accession", "nprot")]


## ----SIn-----------------------------------------------------------------
siquant <- quantify(msexp, method = "SIn")
processingData(siquant)
exprs(siquant)


## ----plotSpectrumSpectrum, dev='pdf', fig.width=6.5, fig.height=6.5------
centroided <- pickPeaks(itraqdata, verbose=FALSE)
(k <- which(fData(centroided)[, "PeptideSequence"] == "TAGIQIVADDLTVTNPK"))
mzk <- precursorMz(centroided)[k]
zk <- precursorCharge(centroided)[k]
mzk * zk
plot(centroided[[k[1]]], centroided[[k[2]]])


## ----compareSpectra, tidy=FALSE------------------------------------------
compareSpectra(centroided[[2]], centroided[[3]],
               fun = "common")
compareSpectra(centroided[[2]], centroided[[3]],
               fun = "cor")
compareSpectra(centroided[[2]], centroided[[3]],
               fun = "dotproduct")


## ----msnexpcompareSpectra------------------------------------------------
compmat <- compareSpectra(centroided, fun="cor")
compmat[1:10, 1:5]


## ----hclustcompareSpectra, dev='pdf', fig.width=5, fig.height=6----------
plot(hclust(as.dist(compmat)))


## ----incompdiss, echo=TRUE, cache=FALSE, tidy=FALSE----------------------
iTRAQ5
incompdiss <- quantify(itraqdata,
                       method = "trap",
                       reporters = iTRAQ5,
                       strict = FALSE,
                       verbose = FALSE)
head(exprs(incompdiss))


## ----incompdissPlot, dev='pdf', fig.width=5, fig.height=2.5, echo=FALSE, warning=FALSE----
dfr <- melt(exprs(incompdiss))
colnames(dfr) <- c("feature", "reporters", "intensity")
dfr$reporters <- sub("iTRAQ5.", "", dfr$reporters)
repsum <- apply(exprs(incompdiss), 1, function(x) sum(x[1:4]))
dfr2 <- data.frame(iTRAQ1to4 = repsum, iTRAQ5 = exprs(incompdiss)[,5])
p1 <- ggplot(data = dfr, aes(x = reporters,y = log10(intensity))) +
  geom_boxplot() +
  theme_gray(6)
p2 <- ggplot(data = dfr2, aes(x = log10(iTRAQ1to4), y = log10(iTRAQ5))) +
  geom_point(alpha = I(1/2)) +
  geom_abline(intercept = 0, slope = 1, linetype = "dotted") +
  stat_smooth(method = lm, se = FALSE) +
  xlab(label = expression(log[10]~sum~114~to~117)) +
  ylab(label = expression(log[10]~145)) +
  theme_gray(6)
grid.newpage()
pushViewport(viewport(layout = grid.layout(1, 2)))
print(p1, vp = vplayout(1, 1))
print(p2, vp = vplayout(1, 2))


## ----makeexp12, echo=TRUE, cache=FALSE, tidy = FALSE---------------------
exp1 <- quantify(itraqdata, reporters = iTRAQ4,
                 verbose = FALSE)
sampleNames(exp1)
exp2 <- quantify(rawdata, reporters = iTRAQ4,
                 verbose = FALSE)
sampleNames(exp2)


## ----updateFnames, echo=TRUE, cache=FALSE--------------------------------
head(featureNames(exp1))
exp1 <- updateFeatureNames(exp1)
head(featureNames(exp1))
head(featureNames(exp2))
exp2 <- updateFeatureNames(exp2)
head(featureNames(exp2))


## ----comb1, echo=TRUE, cache=FALSE---------------------------------------
exp12 <- combine(exp1, exp2)
dim(exp1)
dim(exp2)
dim(exp12)


## ----make2exps2, echo=TRUE, cache=FALSE, tidy=FALSE----------------------
set.seed(1)
i <- sample(length(itraqdata), 35)
j <- sample(length(itraqdata), 35)
exp1 <- quantify(itraqdata[i], reporters = iTRAQ4,
                 verbose = FALSE)
exp2 <- quantify(itraqdata[j], reporters = iTRAQ4,
                 verbose = FALSE)
exp1 <- droplevels(exp1)
exp2 <- droplevels(exp2)
table(featureNames(exp1) %in% featureNames(exp2))
exp1 <- combineFeatures(exp1,
                        groupBy = fData(exp1)$ProteinAccession)
exp2 <- combineFeatures(exp2,
                        groupBy = fData(exp2)$ProteinAccession)
head(featureNames(exp1))
head(featureNames(exp2))


## ----renameSamples, echo=TRUE, cache=FALSE-------------------------------
sampleNames(exp1)
exp1 <- updateSampleNames(exp1)
sampleNames(exp1)
sampleNames(exp1) <- c("Ctrl1", "Cond1", "Ctrl2", "Cond2")
sampleNames(exp2) <- c("Ctrl3", "Cond3", "Ctrl4", "Cond4")


## ----fdatanames, echo=TRUE, cache=FALSE----------------------------------
stopifnot(all(fvarLabels(exp1) == fvarLabels(exp2)))
fData(exp1)["BSA", 1:4]
fData(exp2)["BSA", 1:4]


## ----renameFvars, echo=TRUE, cache=FALSE---------------------------------
exp1 <- updateFvarLabels(exp1)
exp2 <- updateFvarLabels(exp2)
head(fvarLabels(exp1))
head(fvarLabels(exp2))


## ----combine, echo=TRUE, cache=FALSE-------------------------------------
exp12 <- combine(exp1, exp2)
dim(exp12)
pData(exp12)
exprs(exp12)[25:28, ]
exp12


## ----avg-----------------------------------------------------------------
library("pRolocdata")
data(tan2009r1)
data(tan2009r2)
data(tan2009r3)
avgtan <- averageMSnSet(list(tan2009r1, tan2009r2, tan2009r3))
head(exprs(avgtan))
head(fData(avgtan)$disp)
head(fData(avgtan)$nNA)


## ----avg2, dev='pdf', fig.height=5, fig.width=5--------------------------
disp <- rowMax(fData(avgtan)$disp)
disp[disp == 0] <- max(disp)
range(disp)
library("pRoloc")
plot2D(avgtan, cex = 3 * disp)


## ----sessioninfo, results='asis', echo=FALSE, cache=FALSE----------------
toLatex(sessionInfo())