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OpenSwathRTNormalizer

Generic Workflow Nodes for KNIME: OpenMS version 2.6.0.202009301213 by Freie Universitaet Berlin, Universitaet Tuebingen, and the OpenMS Team

This tool will take a description of RT peptides and their normalized retention time to write out a transformation file on how to transform the RT space into the normalized space.

Web Documentation for OpenSwathRTNormalizer

Options

version
Version of the tool that generated this parameters file.
min_rsq
Minimum r-squared of RT peptides regression
min_coverage
Minimum relative amount of RT peptides to keep
estimateBestPeptides
Whether the algorithms should try to choose the best peptides based on their peak shape for normalization. Use this option you do not expect all your peptides to be detected in a sample and too many 'bad' peptides enter the outlier removal step (e.g. due to them being endogenous peptides or using a less curated list of peptides).
log
Name of log file (created only when specified)
debug
Sets the debug level
threads
Sets the number of threads allowed to be used by the TOPP tool
no_progress
Disables progress logging to command line
force
Overrides tool-specific checks
test
Enables the test mode (needed for internal use only)
outlierMethod
Which outlier detection method to use (valid: 'iter_residual', 'iter_jackknife', 'ransac', 'none'). Iterative methods remove one outlier at a time. Jackknife approach optimizes for maximum r-squared improvement while 'iter_residual' removes the datapoint with the largest residual error (removal by residual is computationally cheaper, use this with lots of peptides).
useIterativeChauvenet
Whether to use Chauvenet's criterion when using iterative methods. This should be used if the algorithm removes too many datapoints but it may lead to true outliers being retained.
RANSACMaxIterations
Maximum iterations for the RANSAC outlier detection algorithm.
RANSACMaxPercentRTThreshold
Maximum threshold in RT dimension for the RANSAC outlier detection algorithm (in percent of the total gradient). Default is set to 3% which is around +/- 4 minutes on a 120 gradient.
RANSACSamplingSize
Sampling size of data points per iteration for the RANSAC outlier detection algorithm.
stop_report_after_feature
Stop reporting after feature (ordered by quality; -1 means do not stop).
rt_extraction_window
Only extract RT around this value (-1 means extract over the whole range, a value of 500 means to extract around +/- 500 s of the expected elution). For this to work, the TraML input file needs to contain normalized RT values.
rt_normalization_factor
The normalized RT is expected to be between 0 and 1. If your normalized RT has a different range, pass this here (e.g. it goes from 0 to 100, set this value to 100)
quantification_cutoff
Cutoff in m/z below which peaks should not be used for quantification any more
write_convex_hull
Whether to write out all points of all features into the featureXML
spectrum_addition_method
For spectrum addition, either use simple concatenation or use peak resampling
add_up_spectra
Add up spectra around the peak apex (needs to be a non-even integer)
spacing_for_spectra_resampling
If spectra are to be added, use this spacing to add them up
uis_threshold_sn
S/N threshold to consider identification transition (set to -1 to consider all)
uis_threshold_peak_area
Peak area threshold to consider identification transition (set to -1 to consider all)
scoring_model
Scoring model to use
im_extra_drift
Extra drift time to extract for IM scoring (as a fraction, e.g. 0.25 means 25% extra on each side)
strict
Whether to error (true) or skip (false) if a transition in a transition group does not have a corresponding chromatogram.
stop_after_feature
Stop finding after feature (ordered by intensity; -1 means do not stop).
stop_after_intensity_ratio
Stop after reaching intensity ratio
min_peak_width
Minimal peak width (s), discard all peaks below this value (-1 means no action).
peak_integration
Calculate the peak area and height either the smoothed or the raw chromatogram data.
background_subtraction
Remove background from peak signal using estimated noise levels. The 'original' method is only provided for historical purposes, please use the 'exact' method and set parameters using the PeakIntegrator: settings. The same original or smoothed chromatogram specified by peak_integration will be used for background estimation.
recalculate_peaks
Tries to get better peak picking by looking at peak consistency of all picked peaks. Tries to use the consensus (median) peak border if the variation within the picked peaks is too large.
use_precursors
Use precursor chromatogram for peak picking (note that this may lead to precursor signal driving the peak picking)
use_consensus
Use consensus peak boundaries when computing transition group picking (if false, compute independent peak boundaries for each transition)
recalculate_peaks_max_z
Determines the maximal Z-Score (difference measured in standard deviations) that is considered too large for peak boundaries. If the Z-Score is above this value, the median is used for peak boundaries (default value 1.0).
minimal_quality
Only if compute_peak_quality is set, this parameter will not consider peaks below this quality threshold
resample_boundary
For computing peak quality, how many extra seconds should be sample left and right of the actual peak
compute_peak_quality
Tries to compute a quality value for each peakgroup and detect outlier transitions. The resulting score is centered around zero and values above 0 are generally good and below -1 or -2 are usually bad.
compute_peak_shape_metrics
Calculates various peak shape metrics (e.g., tailing) that can be used for downstream QC/QA.
compute_total_mi
Compute mutual information metrics for individual transitions that can be used for OpenSWATH/IPF scoring.
boundary_selection_method
Method to use when selecting the best boundaries for peaks.
sgolay_frame_length
The number of subsequent data points used for smoothing. This number has to be uneven. If it is not, 1 will be added.
sgolay_polynomial_order
Order of the polynomial that is fitted.
gauss_width
Gaussian width in seconds, estimated peak size.
use_gauss
Use Gaussian filter for smoothing (alternative is Savitzky-Golay filter)
peak_width
Force a certain minimal peak_width on the data (e.g. extend the peak at least by this amount on both sides) in seconds. -1 turns this feature off.
signal_to_noise
Signal-to-noise threshold at which a peak will not be extended any more. Note that setting this too high (e.g. 1.0) can lead to peaks whose flanks are not fully captured.
sn_win_len
Signal to noise window length.
sn_bin_count
Signal to noise bin count.
write_sn_log_messages
Write out log messages of the signal-to-noise estimator in case of sparse windows or median in rightmost histogram bin
remove_overlapping_peaks
Try to remove overlapping peaks during peak picking
method
Which method to choose for chromatographic peak-picking (OpenSWATH legacy on raw data, corrected picking on smoothed chromatogram or Crawdad on smoothed chromatogram).
integration_type
The integration technique to use in integratePeak() and estimateBackground() which uses either the summed intensity, integration by Simpson's rule or trapezoidal integration.
baseline_type
The baseline type to use in estimateBackground() based on the peak boundaries. A rectangular baseline shape is computed based either on the minimal intensity of the peak boundaries, the maximum intensity or the average intensity (base_to_base).
fit_EMG
Fit the chromatogram/spectrum to the EMG peak model.
dia_extraction_window
DIA extraction window in Th or ppm.
dia_extraction_unit
DIA extraction window unit
dia_centroided
Use centroided DIA data.
dia_byseries_intensity_min
DIA b/y series minimum intensity to consider.
dia_byseries_ppm_diff
DIA b/y series minimal difference in ppm to consider.
dia_nr_isotopes
DIA number of isotopes to consider.
dia_nr_charges
DIA number of charges to consider.
peak_before_mono_max_ppm_diff
DIA maximal difference in ppm to count a peak at lower m/z when searching for evidence that a peak might not be monoisotopic.
interpolation_step
Sampling rate for the interpolation of the model function.
tolerance_stdev_bounding_box
Bounding box has range [minimim of data, maximum of data] enlarged by tolerance_stdev_bounding_box times the standard deviation of the data.
max_iteration
Maximum number of iterations using by Levenberg-Marquardt algorithm.
mean
Centroid position of the model.
variance
Variance of the model.
use_shape_score
Use the shape score (this score measures the similarity in shape of the transitions using a cross-correlation)
use_coelution_score
Use the coelution score (this score measures the similarity in coelution of the transitions using a cross-correlation)
use_rt_score
Use the retention time score (this score measure the difference in retention time)
use_library_score
Use the library score
use_elution_model_score
Use the elution model (EMG) score (this score fits a gaussian model to the peak and checks the fit)
use_intensity_score
Use the intensity score
use_nr_peaks_score
Use the number of peaks score
use_total_xic_score
Use the total XIC score
use_total_mi_score
Use the total MI score
use_sn_score
Use the SN (signal to noise) score
use_mi_score
Use the MI (mutual information) score
use_dia_scores
Use the DIA (SWATH) scores. If turned off, will not use fragment ion spectra for scoring.
use_ms1_correlation
Use the correlation scores with the MS1 elution profiles
use_sonar_scores
Use the scores for SONAR scans (scanning swath)
use_ion_mobility_scores
Use the scores for Ion Mobility scans
use_ms1_fullscan
Use the full MS1 scan at the peak apex for scoring (ppm accuracy of precursor and isotopic pattern)
use_ms1_mi
Use the MS1 MI score
use_uis_scores
Use UIS scores for peptidoform identification
InitialQualityCutoff
The initial overall quality cutoff for a peak to be scored (range ca. -2 to 2)
OverallQualityCutoff
The overall quality cutoff for a peak to go into the retention time estimation (range ca. 0 to 10)
NrRTBins
Number of RT bins to use to compute coverage. This option should be used to ensure that there is a complete coverage of the RT space (this should detect cases where only a part of the RT gradient is actually covered by normalization peptides)
MinPeptidesPerBin
Minimal number of peptides that are required for a bin to counted as 'covered'
MinBinsFilled
Minimal number of bins required to be covered

Input Ports

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Input files separated by blank [mzML]
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transition file with the RT peptides ('TraML' or 'csv') [csv,traML]
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RT normalization file (how to map the RTs of this run to the ones stored in the library) [trafoXML,opt.]

Output Ports

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output file [trafoXML]

Views

OpenSwathRTNormalizer Std Output
The text sent to standard out during the execution of OpenSwathRTNormalizer.
OpenSwathRTNormalizer Error Output
The text sent to standard error during the execution of OpenSwathRTNormalizer. (If it appears in gray, it's the output of a previously failing run which is preserved for your trouble shooting.)

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Installation

To use this node in KNIME, install OpenMS from the following update site:

KNIME 4.2
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