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)