Parametric Time Warping aligns patterns, i.e. it aims to put corresponding features at the same locations. The algorithm searches for an optimal polynomial describing the warping. It is possible to align one sample to a reference, several samples to the same reference, or several samples to several references. One can choose between calculating individual warpings, or one global warping for a set of samples and one reference. Two optimization criteria are implemented: RMS (Root Mean Square error) and WCC (Weighted Cross Correlation). Both warping of peak profiles and of peak lists are supported.
|Author||Jan Gerretzen <firstname.lastname@example.org>, Paul Eilers <email@example.com>, Hans Wouters, Tom Bloemberg <firstname.lastname@example.org>, Ron Wehrens <email@example.com>|
|Date of publication||2015-08-21 11:48:26|
|Maintainer||Ron Wehrens <firstname.lastname@example.org>|
|License||GPL (>= 2)|
asysm: Trend estimation with asymmetric least squares
baseline.corr: Baseline Correction using asymmetric least squares
bestref: Identification of optimal reference
calc.multicoef: Calculation of warping coefficients when applying more than...
calc.zerocoef: Correction for warping coefficients when using zeropadding
coda: Chromatogram selection using the CODA algorithm
difsm: Smoothing with a finite difference penalty
gaschrom: 16 calibration GC traces
lcms: Parts of 3 proteomic LC-MS samples
mzchannel2pktab: Conversion between peak lists from hyphenated MS (LCMS, GCMS,...
padzeros: Pad matrix with zeros
plot.ptw: Plot a ptw object
predict.ptw: Prediction of warped signals
ptw: Parametric Time Warping
ptwgrid: Calculate RMS or WCC values on a grid
RMS: Quality criteria for comparing patterns with shifts
select.traces: Select traces from a data set according to several criteria
warp.time: Transform time according to a given warping function
wcc: Weighted auto- and cross-correlation measures
whit1: Weighted Whittaker smoothing with a first order finite...
whit2: Weighted Whittaker smoothing with a second order finite...