View source: R/optimizeRetCorGroupParameters.R
optimizeRetGroup | R Documentation |
This function provides optimisation for parameters of the xcms-method retcor.obiwarp and group.density. The retention time correction is optimised by minimizing intra-feature retention time shifts; grouping is optimized by increasing the number of features which have exactly one peak per sample.
optimizeRetGroup(xset, params = getDefaultRetGroupStartingParams(), nSlaves = 4, subdir = "IPO", plot = TRUE)
xset |
|
params |
A list of parameters which are needed by xcms-methods retcor.obiwarp and group.density. List-items with two values will be optimized. The first value defines the lower test value, the second one the higher test value. |
nSlaves |
Number of slaves the optimization process should spawn. |
subdir |
The name of the subdirectory which is created and where the figures of the response
surface models will be saved to. |
plot |
Defines if plots should be generated ( |
This function provides optimisation for parameters of the xcms-method retcor.obiwarp and group.density. The retention time correction is optimised by minimizing intra-feature retention time shifts; grouping is optimized by increasing the number of features which have exactly one peak per sample.
A LIST of length n+1 with n beeing the optimization runs needed
comp1-comp(n) |
A LIST containing: |
comp(n+1) |
A LIST containing: |
Gunnar Libiseller
Obiwarp
Prince, J. T., & Marcotte, E. M. (2006). Chromatographic alignment of
ESI-LC-MS proteomics data sets by ordered bijective interpolated warping.
Analytical chemistry, 78(17), 6140-52. doi:10.1021/ac0605344
getDefaultRetGroupStartingParams
mtbls2files <- list.files(file.path(find.package("mtbls2"), "mzML"), full.names=TRUE) params <- list(min_peakwidth=12, max_peakwidth=30, ppm=30, mzdiff=-0.001, snthresh=10, noise=10000, prefilter=3, value_of_prefilter=100, mzCenterFun="wMean", integrate=1, fitgauss=FALSE, verbose.columns=FALSE, nSlaves=2) xset <- calculateXcmsSet(mtbls2files[1:2], params) #optimize the retention time correction and grouping parameters paramsRG <- getDefaultRetGroupStartingParams() paramsRG$profStep <- 1 paramsRG$minfrac <- 0.75 resultRG <- optimizeRetGroup(xset, params=paramsRG, nSlaves=4,subdir="mtbls2") writeRScript(params, resultRG$best_settings, 4)
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