View source: R/profileSummarize.R
profileSummarize | R Documentation |
ProfileSummarize calculates mean and SE for each channel in each protein or peptide profile using a random effect model (proteins) or arithmetic mean (peptides). A random effect model can avoid dominance of a peptide with a large number spectra. See Tutorial 6 for details.
profileSummarize(
protsCombineCnew,
numRefCols,
numDataCols,
refColsKeep = c(1, 2),
eps,
GroupBy = "protId",
outlierExclude = "spectraAndPeptide",
setSeed = NULL,
set.seed = NULL,
cpus = NULL,
multiprocess = FALSE,
singularList = FALSE
)
protsCombineCnew |
data frame of profiles (spectra or spectra and peptides) with outlier information |
numRefCols |
number of columns preceding the profile data |
numDataCols |
number of fractions in each profile |
refColsKeep |
which reference columns to keep (requires columns 1 and 2 for protein and peptide name) |
eps |
small value to add so that log argument is greater than zero |
GroupBy |
‘protId’ if average peptides to give mean protein profile; ‘peptideId’ if average spectra to give mean peptide profiles |
outlierExclude |
'none', 'spectra', or 'spectraAndpeptide' (default) according to exclusion level |
setSeed |
NULL (default) deprecated; see note for "cpus" |
set.seed |
NULL (default) deprecated; see note for "cpus" |
cpus |
NULL (default); deprecated Use BiocParallel with SnowParm or other multiprocessor method to set number of processors See examples for how to specify the number of processors |
multiprocess |
FALSE by default |
singularList |
if TRUE, list fractions associated with a given protein or peptide with singular fit from the random effects function lmer; default is FALSE |
Mean or weighted mean NSA profiles
set.seed(17356) # this works if multiprocess is set to FALSE
eps <- 0.029885209
data(spectraNSA_test)
flagSpectraBox <- outlierFind(protClass=spectraNSA_test,
outlierLevel='peptide', numRefCols=5, numDataCols=9,
outlierMeth='boxplot', range=3, eps=eps,
randomError=TRUE, multiprocess=FALSE)
pepProfiles <- profileSummarize(protsCombineCnew=flagSpectraBox,
numRefCols=6, numDataCols=9, refColsKeep=c(1,2,4),eps=eps,
GroupBy='peptideId', outlierExclude='spectra',
multiprocess=FALSE)
str(pepProfiles, strict.width='cut', width=65)
# Now use multiple processors with specified random number seed
snowParam <- BiocParallel::SnowParam(workers = 2, RNGseed=92883)
#
# now modifiy the existing BiocParallelParam
BiocParallel::register(snowParam, default=FALSE)
pepProfilesM <- profileSummarize(protsCombineCnew=flagSpectraBox,
numRefCols=6, numDataCols=9, refColsKeep=c(1,2,4),eps=eps,
GroupBy='peptideId', outlierExclude='spectra',
multiprocess=TRUE)
str(pepProfilesM, strict.width='cut', width=65)
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