Nothing
library("protiq")
data(leptoSRM)
## reading data and checking input
dataTest <- new("scampi", peptides=leptoSRMpeptides,
proteins=leptoSRMproteins, edgespp=leptoSRMedgespp)
if (nrow(dataTest@peptides) != 151 ||
nrow(dataTest@proteins) != 39 ||
nrow(dataTest@edgespp) != 151) {
stop("Error by reading input data or building 'scampi' object.")
}
dataChecked <-
checkInputData(new("scampi", peptides=leptoSRMpeptides,
proteins=leptoSRMproteins, edgespp=leptoSRMedgespp),
rescaling=FALSE)
if (nrow(dataChecked@peptides) != 151 ||
nrow(dataChecked@proteins) != 39 ||
nrow(dataChecked@edgespp) != 151) {
stop("Error by input data checking.")
}
## building the graph structure, extracting information from graph
ppGraph <- protiq:::buildBipartiteGraph(nrow(dataChecked@peptides),
nrow(dataChecked@proteins),
dataChecked@edgespp)
protiq:::getMyProteins(1, dataChecked@edgespp)
protiq:::getDmat(c(1,2,3,7,8,24), dataChecked@edgespp)
protiq:::getMyNeighborhoodSize(8, group="peptides", dataChecked@edgespp)
## decompose graph in connected components and work with these
ppComponents <- RBGL:::connectedComp(ppGraph)
testCC <-
protiq:::preprocessCC(ppComponents[[1]], dataChecked@peptides,
dataChecked@edgespp, nrow(dataChecked@peptides))
ppComponents <-
lapply(ppComponents, protiq:::preprocessCC, dataChecked@peptides,
dataChecked@edgespp, nrow(dataChecked@peptides))
protiq:::isInCC(3, 21, group="peptides", ppComponents)
protiq:::getMyCCNr(24, "peptides", ppComponents)
## preprocessing the input data
tmpPrepro <- preprocessInputData(dataChecked)
dataPrepro <- tmpPrepro[["dataPrepro"]]
ppGraph <- tmpPrepro[["ppGraph"]]
ppComponents <- tmpPrepro[["ccList"]]
rm("tmpPrepro")
## class for output
dataOutTest <-
new("scampiVal", peptides=dataChecked@peptides,
proteins=dataChecked@proteins,
edgespp=dataChecked@edgespp, parameters=list(),
ppGraph=ppGraph, ccList=ppComponents)
## parameter estimation
protiq:::getSampleCov(ppComponents[[4]],
myMean=rep(3,nrow(dataPrepro@peptides)))
lseparam <- protiq:::estimateLSEparam(dataPrepro@peptides, ppComponents)
getCovU(ppComponents[[4]], beta=1, tau=0.2)
protiq:::getCCnlL(getCovU(ppComponents[[4]], beta=1, tau=0.2),
c(0.5,1,2,0.2))
scampiParam <- estimateModelParameters(method="LSE", ppComponents,
peptides=dataPrepro@peptides,
numIter=3)
estimateModelParameters(method="LSE", ppComponents,
peptides=dataPrepro@peptides)
## quantify proteins and reassess peptides
ppComponents <- lapply(ppComponents, getCovU,
beta=scampiParam[["LSE"]]["betaH"],
tau=scampiParam[["LSE"]]["tauH"])
quantifyProtein(dataPrepro@proteins[1,c("protId","ccInd")], ppComponents,
scampiParam[["LSE"]])
quantifyPeptide(dataPrepro@peptides[1,c("pepId","ccInd")], ppComponents,
scampiParam[["LSE"]])
scampiOut <- quantifyProteins(dataPrepro, ppComponents, scampiParam,
quantifyPeptides=TRUE)
## test of the two main functions
showProc.time <- local({
pct <- proc.time()
function() { ## CPU elapsed __since last called__
ot <- pct ; pct <<- proc.time()
cat('Time elapsed: ', (pct - ot)[1:3],'\n')
}
})
scampiTest <-
runScampi(leptoSRMpeptides, leptoSRMproteins, leptoSRMedgespp,
rescaling=FALSE, method="LSE", quantifyPeptides=TRUE,
numIter=3, verbose=FALSE)
showProc.time()
scampiIterateTest <-
iterateScampi(leptoSRMpeptides, leptoSRMproteins, leptoSRMedgespp,
rescaling=FALSE, method="LSE", numIter=3, thresh=1.73,
verbose=FALSE)
showProc.time()
## commented for time reasons (keep test brief):
#mleparam <- protiq:::estimateMLEparam(c(0.1,0.31,3,0.1), ppComponents)
#scampiParam <- estimateModelParameters(method="all", ppComponents,
# peptides=dataPrepro@peptides,
# numIter=3)
#estimateModelParameters(method="MLE", ppComponents,numIter=3)
#scampiTest <-
# runScampi(leptoSRMpeptides, leptoSRMproteins, leptoSRMedgespp,
# rescaling=FALSE, method="all", quantifyPeptides=TRUE,
# numIter=3, verbose=FALSE)
#showProc.time()
#scampiIterateTest <-
# iterateScampi(leptoSRMpeptides, leptoSRMproteins, leptoSRMedgespp,
# rescaling=FALSE, method="MLE", numIter=3,
# numMLEIter=3, thresh=1.73, verbose=FALSE)
#showProc.time()
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