profileSummarize: protProfileSummarize calculates mean and SE for each channel...

In mooredf22/protlocassign0p1p1: Compute constrained proportional assignments for fractionated protein abundance

Description

protProfileSummarize calculates mean and SE for each channel in each prot using random effect model or arithmetic mean random effect model can avoid dominance of a sequence with too many spectra

Usage

profileSummarize(
  protsCombineCnew,
  numRefCols,
  numDataCols,
  refColsKeep = c(1, 2),
  eps,
  GroupBy = "protId",
  outlierExclude = "spectraAndPeptide",
  cpus = 1
)

Arguments

protsCombineCnew	a matrix of protein information and normalized specific amounts and outlier information
numRefCols	number of columns before Mass Spectrometry data columns
numDataCols	how many columns in MS data
refColsKeep	which reference (non-data) columns to keep
eps	epsilon to avoid log(0)
GroupBy	"protId" if average by protein; "peptideId" if average by peptide
outlierExclude	"none", "spectra", or "spectraAndpeptide" (default) according to exclusion level
cpus	number of cpus to use for parallel processing

Value

protProfileSummaryIdentity: mean or weighted mean normalized specific amount profiles

Examples

set.seed(17356)
eps <- 0.029885209
flagSpectraBox <- outlierFind(protClass=TLN1_test,
                              outlierLevel="peptide", numRefCols=5, numDataCols=9,
                              outlierMeth="boxplot", range=3, eps=eps,
                              cpus=1, randomError=TRUE)
# examine numbers of spectra that are outliers
table(flagSpectraBox$outlier.num.spectra)
pepProfiles <- profileSummarize(protsCombineCnew=flagSpectraBox,
                                numRefCols=6, numDataCols=9, refColsKeep=c(1,2,4),eps=eps,
                                GroupBy="peptideId", outlierExclude="spectra")
str(pepProfiles, strict.width="cut", width=65)

mooredf22/protlocassign0p1p1 documentation built on Feb. 7, 2022, 1:55 a.m.