View source: R/do_adjustRtime-functions.R
do_adjustRtime_peakGroups | R Documentation |
The function performs retention time correction by assessing
the retention time deviation across all samples using peak groups
(features) containg chromatographic peaks present in most/all samples.
The retention time deviation for these features in each sample is
described by fitting either a polynomial (smooth = "loess"
) or
a linear (smooth = "linear"
) model to the data points. The
models are subsequently used to adjust the retention time for each
spectrum in each sample.
do_adjustRtime_peakGroups(peaks, peakIndex, rtime, minFraction = 0.9,
extraPeaks = 1, smooth = c("loess", "linear"), span = 0.2,
family = c("gaussian", "symmetric"), peakGroupsMatrix = matrix(ncol =
0, nrow = 0), subset = integer(), subsetAdjust = c("average",
"previous"))
peaks |
a |
peakIndex |
a |
rtime |
a |
minFraction |
|
extraPeaks |
|
smooth |
character defining the function to be used, to interpolate
corrected retention times for all peak groups. Either |
span |
|
family |
character defining the method to be used for loess smoothing.
Allowed values are |
peakGroupsMatrix |
optional |
subset |
|
subsetAdjust |
|
The alignment bases on the presence of compounds that can be found
in all/most samples of an experiment. The retention times of individual
spectra are then adjusted based on the alignment of the features
corresponding to these house keeping compounds. The paraneters
minFraction
and extraPeaks
can be used to fine tune which
features should be used for the alignment (i.e. which features
most likely correspond to the above mentioned house keeping compounds).
Parameter subset
allows to define a subset of samples within the
experiment that should be aligned. All samples not being part of the subset
will be aligned based on the adjustment of the closest sample within the
subset. This allows to e.g. exclude blank samples from the alignment process
with their retention times being still adjusted based on the alignment
results of the real samples.
A list
with numeric
vectors with the adjusted
retention times grouped by sample.
The method ensures that returned adjusted retention times are increasingly ordered, just as the raw retention times.
Colin Smith, Johannes Rainer
Colin A. Smith, Elizabeth J. Want, Grace O'Maille, Ruben Abagyan and Gary Siuzdak. "XCMS: Processing Mass Spectrometry Data for Metabolite Profiling Using Nonlinear Peak Alignment, Matching, and Identification" Anal. Chem. 2006, 78:779-787.
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