quantifyPeptide: Compute expected value for the peptide abundance.

In protiq: Protein (identification and) quantification based on peptide evidence

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.

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.

Value

Expected value of the peptide abundance (see details).

Note

This function is intended to assess a single peptide when the parameter values have been computed previously. To run a whole analysis (check input data, preprocess connected components, estimate model parameters and compute abundance sore estimates) you should use the function runScampi or iterateScampi.

Author(s)

Sarah Gerster [e-mail]

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))

protiq documentation built on May 2, 2019, 9:06 a.m.