protiq (version 1.2)

quantifyPeptide: Compute expected value for the peptide abundance.

Description

Use provided model parameter values to compute the expected value of the abundance for a given petpitde. This value can the be compared to the originally measure value to identify outliers in the input data.

Usage

quantifyPeptide(pepInfo, ccList, param, verbose = FALSE)

Arguments

pepInfo

Vector with two elements: pepId and index of connected component (in list ccList) which contains pepId.

ccList

List of pre-processed connected components.

param

Vector with at least four named elements: alphaH, betaH, muH and tauH (estimates for the four model parameters).

verbose

If TRUE, detailed output is provided.

Value

Expected value of the peptide abundance (see details).

Details

In order to avoid overfitting, the value computed by this function E[U_k|U_i-k], hence the kth measurement is not used to predict the expected value of peptide k.

See Also

runScampi, iterateScampi

Examples

## get data
data("leptoSRM")
## check input data
dataChecked <- checkInputData(scampiData=scampi(peptides=leptoSRMpeptides, 
                                                proteins=leptoSRMproteins,
                                                edgespp=leptoSRMedgespp),
                              rescaling=FALSE)
## preprocess input data
tmpPrepro <- preprocessInputData(scampiData=dataChecked) 
dataPrepro <- tmpPrepro[["dataPrepro"]]
myCCList <- tmpPrepro[["ccList"]]
rm(tmpPrepro)	

## compute covariance matrices
myCCList <- lapply(myCCList, getCovU,
                   beta=0.2,
                   tau=0.5)

## compute expected value of abundance for peptide 13
pepAbundanceScore <- 
  quantifyPeptide(pepInfo=dataPrepro@peptides[13, c("pepId", "ccInd")], 
                  ccList=myCCList, param=c(alphaH=0, betaH=0.2, muH=0.3, 
                  tauH=0.2))