| ncGTWalign {ncGTW} | R Documentation |
This function applies ncGTW alignment to the input feature.
ncGTWalign(ncGTWinput, xcmsLargeWin, parSamp = 10, k1Num = 3, k2Num = 1, bpParam = BiocParallel::SnowParam(workers = 1), ncGTWparam = NULL)
ncGTWinput |
A |
xcmsLargeWin |
A |
parSamp |
Decide how many samples are in each group when considering parallel computing, and the default is 10. |
k1Num |
Decide how many different k1 will be tested in stage 1. The default is 3. |
k2Num |
Decide how many different k2 will be tested in stage 2. The default is 1. |
bpParam |
A object of BiocParallel to control parallel processing,
and can be created by
|
ncGTWparam |
A |
This function realign the input feature with ncGTW alignment function with given m/z and RT range.
A ncGTWoutput object.
# obtain data
data('xcmsExamples')
xcmsLargeWin <- xcmsExamples$xcmsLargeWin
xcmsSmallWin <- xcmsExamples$xcmsSmallWin
ppm <- xcmsExamples$ppm
# detect misaligned features
excluGroups <- misalignDetect(xcmsLargeWin, xcmsSmallWin, ppm)
# obtain the paths of the sample files
filepath <- system.file("extdata", package = "ncGTW")
file <- list.files(filepath, pattern="mzxml", full.names=TRUE)
tempInd <- matrix(0, length(file), 1)
for (n in seq_along(file)){
tempCha <- file[n]
tempLen <- nchar(tempCha)
tempInd[n] <- as.numeric(substr(tempCha, regexpr("example", tempCha) + 7,
tempLen - 6))
}
# sort the paths by data acquisition order
file <- file[sort.int(tempInd, index.return = TRUE)$ix]
## Not run:
# load the sample profiles
ncGTWinputs <- loadProfile(file, excluGroups)
# initialize the parameters of ncGTW alignment with default
ncGTWparam <- new("ncGTWparam")
# run ncGTW alignment
ncGTWoutputs <- vector('list', length(ncGTWinputs))
for (n in seq_along(ncGTWinputs))
ncGTWoutputs[[n]] <- ncGTWalign(ncGTWinputs[[n]], xcmsLargeWin, 5,
ncGTWparam = ncGTWparam)
## End(Not run)