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required parameter

advanced parameter

+MapAlignerSpectrumCorrects retention time distortions between maps by spectrum alignment.

version1.10.0 Version of the tool that generated this parameters file.

++1Instance '1' section for 'MapAlignerSpectrum'

in[] Input files separated by blanks (all must have the same file type)input file*.mzML

out[] Output files separated by blanks. Either 'out' or 'trafo_out' has to be provided. They can be used together.output file*.mzML

trafo_out[] Transformation output files separated by blanks. Either 'out' or 'trafo_out' has to be provided. They can be used together.output file*.trafoXML

log Name of log file (created only when specified)

debug0 Sets the debug level

threads1 Sets the number of threads allowed to be used by the TOPP tool

no_progressfalse Disables progress logging to command linetrue,false

testfalse Enables the test mode (needed for internal use only)true,false

+++algorithmAlgorithm parameters section

gapcost1 This Parameter stands for the cost of opining a gap in the Alignment. A Gap means that one Spectrum can not be aligned directly to another Spectrum in the Map. This happens, when the similarity of both spectra a too low or even not present. Imagen as a insert or delete of the spectrum in the map. The gap is necessary for aligning, if we open a gap there is a possibility that an another spectrum can be correct aligned with a higher score as before without gap. But to open a gap is a negative event and has to be punished a bit, so such only in case it 's a good choice to open a gap, if the score is bad enough. The Parameter is to giving as a positive number, the implementation convert it to a negative number.0:∞

affinegapcost0.5 This Parameter controls the cost of extension a already open gap. The idea behind the affine gapcost lies under the assumption, that it is better to get a long distance of connected gaps than to have a structure gap match gap match. There for the punishment for the extension of a gap has to be lower than the normal gapcost. If the the result of the aligmnet show high compression, it is a good idea to lower the affine gapcost or the normal gapcost.0:∞

cutoff_score0.7 The Parameter defines the threshold which filtered Spectra, these Spectra are high potential candidate for deciding the interval of a sub-alignment. Only those pair of Spectra are selected, which has a score higher or same of the threshold.0:1

bucketsize100 Defines the numbers of buckets. It is a quantize of the interval of those points, which defines the main alignment(match points). These points have to filtered, to reduce the amount of points for the calculating a smoother spline curve.1:∞

anchorpoints100 Defines the percent of numbers of match points which a selected from one bucket. The high score pairs are previously selected. The reduction of match points helps to get a smoother spline curve.1:100

debugfalse active the debug mode, there a files written starting with debug prefix.true,false

mismatchscore-5 Defines the score of two Spectra if they have no similarity to each other. -∞:0

scorefunctionSteinScottImproveScore The score function is the core of an alignment. The success of an alignment depends mostly of the elected score function. The score function return the similarity of two Spectrum back. The score influence defines later the way of possible traceback. There exist many way of algorithm to calculate the score.SteinScottImproveScore,ZhangSimilarityScore

+++modelOptions to control the modeling of retention time transformations from data

typeinterpolated Type of modellinear,b_spline,interpolated

++++linearParameters for 'linear' model

symmetric_regressionfalse Perform linear regression on 'y - x' vs. 'y + x', instead of on 'y' vs. 'x'.true,false

++++b_splineParameters for 'b_spline' model

num_breakpoints5 Number of breakpoints of the cubic spline in the smoothing step. More breakpoints mean less smoothing. Reduce this number if the transformation has an unexpected shape.2:∞

break_positionsuniform How to distribute the breakpoints on the retention time scale. 'uniform': intervals of equal size; 'quantiles': equal number of data points per interval.uniform,quantiles

++++interpolatedParameters for 'interpolated' model

interpolation_typecspline Type of interpolation to apply.linear,cspline,akima