| OpenMS 2.5.0

MSSimulator

A highly configurable simulator for mass spectrometry experiments.

This implementation is described in

Bielow C, Aiche S, Andreotti S, Reinert K
MSSimulator: Simulation of Mass Spectrometry Data
Journal of Proteome Research (2011), DOI: 10.1021/pr200155f

The most important features are:

- Simulation of Capillary electrophoresis and HPLC as separation step
- Simulation of MS spectra
- Simulation of MS/MS spectra with configurable precursor-selection strategy
- Simulation of iTRAQ labels
- Simulation of different noise models and instrument types (resolution, peak shape)

Look at the INI file (via "MSSimulator -write_ini myini.ini") to see the available parameters and more functionality.

### Input: FASTA files

Protein sequences (including amino acid modifications) can be provided as FASTA file. We allow a special tag in the description of each entry to specify protein abundance. If you want to create a complex FASTA file with a Gaussian protein abundance model in log space, see our Python script shipping with your OpenMS installation (e.g., <OpenMS-dir>/share/OpenMS/examples/simulation/FASTAProteinAbundanceSampling.py). It supports (random) sampling from a large FASTA file, protein weight filtering and adds an intensity tag to each entry.

If multiplexed data is simulated (like SILAC or iTRAQ) you need to supply multiple FASTA input files. For the label-free setting, all FASTA input files will be merged into one, before simulation.

For MS/MS simulation only a test model is shipped with OpenMS.
Please find trained models at: http://sourceforge.net/projects/open-ms/files/Supplementary/Simulation/.

To specify intensity values for certain proteins, add an abundance tag for the corresponding protein in the FASTA input file:

- add '[# <key>=<value> #]' at the end of the > line to specify intensity For RT control (disable digestion, to make this work!)
  - rt (subjected to small local error by randomization)
  - RT (used as is without local error)

For amino acid modifications, insert their name at the respective amino acid residues. The modifications are fixed. If you need variable modifications, you have to add the desired combinatorial variants (presence/absence of one or all modifications) to the FASTA file. Valid modification names are listed in many TOPP/UTILS, e.g MSGFPlusAdapter 's -fixed_modifications parameter.

e.g.

>seq1 optional comment [# intensity=567.4 #]
(Acetyl).M(Oxidation)ASQYLATARHGC(Carbamidomethyl)FLPRHRDTGILP
>seq2 optional comment [# intensity=117.4, RT=405.3 #]
QKRPSQRHGLATAC(Carbamidomethyl)RHGTGGGDRAT.(Dehydrated)

The command line parameters of this tool are:

    MSSimulator -- A highly configurable simulator for mass spectrometry experiments.

    Full documentation: http://www.openms.de/documentation/UTILS_MSSimulator.html

    Version: 2.5.0-GIT-NOTFOUND-GIT-NOTFOUND Sep 10 2020, 12:20:39, Revision: GIT-NOTFOUND

    To cite OpenMS:

      Rost HL, Sachsenberg T, Aiche S, Bielow C et al.. OpenMS: a flexible open-source software platform for mass spectrometry data analysis. Nat Meth. 2016; 13, 9: 741-748. doi:10.1038/nmeth.3959.

    To cite MSSimulator:

      Bielow C, Aiche S, Andreotti S, Reinert K. MSSimulator: Simulation of Mass Spectrometry Data. J. Proteome Res. 2011; 10, 7:2922-2929. doi:10.1021/pr200155f.

    Usage:

      MSSimulator <options>

    This tool has algorithm parameters that are not shown here! Please check the ini file for a detailed descript

    ion or use the --helphelp option.

    Options (mandatory options marked with '*'):

      -in <files>*       Input protein sequences (valid formats: 'FASTA')

      -out <file>        Output: simulated MS raw (profile) data (valid formats: 'mzML')

      -out_pm <file>     Output: ground-truth picked (centroided) MS data (valid formats: 'mzML')

      -out_fm <file>     Output: ground-truth features (valid formats: 'featureXML')

      -out_cm <file>     Output: ground-truth features, grouping ESI charge variants of each parent peptide (vali

                         d formats: 'consensusXML')

      -out_lcm <file>    Output: ground-truth features, grouping labeled variants (valid formats: 'consensusXML')

      -out_cntm <file>   Output: ground-truth features caused by contaminants (valid formats: 'featureXML')

      -out_id <file>     Output: ground-truth MS2 peptide identifications (valid formats: 'idXML')

    Common UTIL options:

      -ini <file>        Use the given TOPP INI file

      -threads <n>       Sets the number of threads allowed to be used by the TOPP tool (default: '1')

      -write_ini <file>  Writes the default configuration file

      --help             Shows options

      --helphelp         Shows all options (including advanced)

    The following configuration subsections are valid:

     - algorithm   Algorithm parameters section

    You can write an example INI file using the '-write_ini' option.

    Documentation of subsection parameters can be found in the doxygen documentation or the INIFileEditor.

    For more information, please consult the online documentation for this tool:

      - http://www.openms.de/documentation/UTILS_MSSimulator.html

INI file documentation of this tool:

Legend:
required parameter
advanced parameter
+MSSimulator A highly configurable simulator for mass spectrometry experiments.
version 2.5.0-GIT-NOTFOUND-GIT-NOTFOUND Version of the tool that generated this parameters file.
++1 Instance '1' section for 'MSSimulator'
in[] Input protein sequences input file*.FASTA
out output: simulated MS raw (profile) data output file*.mzML
out_pm output: ground-truth picked (centroided) MS data output file*.mzML
out_fm output: ground-truth features output file*.featureXML
out_cm output: ground-truth features, grouping ESI charge variants of each parent peptide output file*.consensusXML
out_lcm output: ground-truth features, grouping labeled variants output file*.consensusXML
out_cntm output: ground-truth features caused by contaminants output file*.featureXML
out_id output: ground-truth MS2 peptide identifications output file*.idXML
log Name of log file (created only when specified)
debug 0 Sets the debug level
threads 1 Sets the number of threads allowed to be used by the TOPP tool
no_progress false Disables progress logging to command line true,false
force false Overwrite tool specific checks.true,false
test false Enables the test mode (needed for internal use only)true,false
+++algorithm Algorithm parameters section
++++MSSim
+++++Digestion
enzyme Trypsin Enzyme to use for digestion (select 'no cleavage' to skip digestion)Asp-N,Chymotrypsin,Asp-N/B,Asp-N_ambic,Trypsin,Arg-C,Arg-C/P,Glu-C+P,V8-DE,TrypChymo,CNBr,no cleavage,PepsinA,Alpha-lytic protease,2-iodobenzoate,iodosobenzoate,staphylococcal protease/D,cyanogen-bromide,Chymotrypsin/P,Lys-C/P,glutamyl endopeptidase,proline-endopeptidase/HKR,Clostripain/P,Lys-N,proline endopeptidase,elastase-trypsin-chymotrypsin,V8-E,Formic_acid,Trypsin/P,unspecific cleavage,Lys-C,leukocyte elastase,PepsinA + P
model naive The cleavage model to use for digestion. 'Trained' is based on a log likelihood model (see DOI:10.1021/pr060507u).trained,naive
min_peptide_length 3 Minimum peptide length after digestion (shorter ones will be discarded)1:∞
++++++model_trained
threshold 0.5 Model threshold for calling a cleavage. Higher values increase the number of cleavages. -2 will give no cleavages, +4 almost full cleavage.-2.0:4.0
++++++model_naive
missed_cleavages 1 Maximum number of missed cleavages considered. All possible resulting peptides will be created.0:∞
+++++RT
rt_column HPLC Modelling of an RT or CE column none,HPLC,CE
auto_scale true Scale predicted RT's/MT's to given 'total_gradient_time'? If 'true', for CE this means that 'CE:lenght_d', 'CE:length_total', 'CE:voltage' have no influence.true,false
total_gradient_time 2500.0 The duration [s] of the gradient.1.0e-05:∞
sampling_rate 2.0 Time interval [s] between consecutive scans 0.01:60.0
++++++scan_window
min 500.0 Start of RT Scan Window [s]0.0:∞
max 1500.0 End of RT Scan Window [s]1.0:∞
++++++variation Random component that simulates technical/biological variation
feature_stddev 3 Standard deviation of shift in retention time [s] from predicted model (applied to every single feature independently)
affine_offset 0 Global offset in retention time [s] from predicted model
affine_scale 1 Global scaling in retention time from predicted model
++++++column_condition
distortion 0 Distortion of the elution profiles. Good presets are 0 for a perfect elution profile, 1 for a slightly distorted elution profile etc... For trapping instruments (e.g. Orbitrap) distortion should be >4.0:10
++++++profile_shape
+++++++width Width of the EGH elution shape, i.e. the sigma^2 parameter, which is computed using 'value' + rnd_cauchy('variance')
value 9.0 Width of the Exponential Gaussian Hybrid distribution shape of the elution profile. This does not correspond directly to the width in [s].0.0:∞
variance 1.6 Random component of the width (set to 0 to disable randomness), i.e. scale parameter for the lorentzian variation of the variance (Note: The scale parameter has to be >= 0).0.0:∞
+++++++skewness Skewness of the EGH elution shape, i.e. the tau parameter, which is computed using 'value' + rnd_cauchy('variance')
value 0.1 Asymmetric component of the EGH. Higher absolute(!) values lead to more skewness (negative values cause fronting, positive values cause tailing). Tau parameter of the EGH, i.e. time constant of the exponential decay of the Exponential Gaussian Hybrid distribution shape of the elution profile.
variance 0.3 Random component of skewness (set to 0 to disable randomness), i.e. scale parameter for the lorentzian variation of the time constant (Note: The scale parameter has to be > 0).0.0:∞
++++++HPLC
model_file examples/simulation/RTPredict.model SVM model for retention time prediction
++++++CE
pH 3.0 pH of buffer 0.0:14.0
alpha 0.5 Exponent Alpha used to calculate mobility 0.0:1.0
mu_eo 0.0 Electroosmotic flow 0.0:5.0
lenght_d 70.0 Length of capillary [cm] from injection site to MS 0.0:1000.0
length_total 75.0 Total length of capillary [cm]0.0:1000.0
voltage 1000.0 Voltage applied to capillary 0.0:∞
+++++Detectability
dt_simulation_on false Modelling detectibility enabled? This can serve as a filter to remove peptides which ionize badly, thus reducing peptide count true,false
min_detect 0.5 Minimum peptide detectability accepted. Peptides with a lower score will be removed
dt_model_file examples/simulation/DTPredict.model SVM model for peptide detectability prediction
+++++Ionization
++++++esi
ionized_residues[Arg, Lys, His] List of residues (as three letter code) that will be considered during ES ionization. The N-term is always assumed to carry a charge. This parameter will be ignored during MALDI ionization Ala,Cys,Asp,Glu,Phe,Gly,His,Ile,Lys,Leu,Met,Asn,Pro,Gln,Arg,Sec,Ser,Thr,Val,Trp,Tyr
charge_impurity[H+:1] List of charged ions that contribute to charge with weight of occurrence (their sum is scaled to 1 internally), e.g. ['H:1'] or ['H:0.7' 'Na:0.3'], ['H:4' 'Na:1'] (which internally translates to ['H:0.8' 'Na:0.2'])
max_impurity_set_size 3 Maximal #combinations of charge impurities allowed (each generating one feature) per charge state. E.g. assuming charge=3 and this parameter is 2, then we could choose to allow '3H+, 2H+Na+' features (given a certain 'charge_impurity' constraints), but no '3H+, 2H+Na+, 3Na+'
ionization_probability 0.8 Probability for the binomial distribution of the ESI charge states
++++++maldi
ionization_probabilities[0.9, 0.1, 0.0] List of probabilities for different charge states (starting at charge=1, 2, ...) during MALDI ionization (the list must sum up to 1.0)
++++++mz
lower_measurement_limit 200.0 Lower m/z detector limit 0.0:∞
upper_measurement_limit 1200.0 Upper m/z detector limit 0.0:∞
+++++RawSignal
enabled true Enable RAW signal simulation? (select 'false' if you only need feature-maps)true,false
peak_shape Gaussian Peak Shape used around each isotope peak (be aware that the area under the curve is constant for both types, but the maximal height will differ (~ 2:3 = Lorentz:Gaussian) due to the wider base of the Lorentzian Gaussian,Lorentzian
++++++resolution
value 50000 Instrument resolution at 400 Th
type linear How does resolution change with increasing m/z?! QTOFs usually show 'constant' behavior, FTs have linear degradation, and on Orbitraps the resolution decreases with square root of mass constant,linear,sqrt
++++++baseline Baseline modeling for MALDI ionization
scaling 0.0 Scale of baseline. Set to 0 to disable simulation of baseline 0.0:∞
shape 0.5 The baseline is modeled by an exponential probability density function (pdf) with f(x) = shape*e^(- shape*x)0.0:∞
++++++mz
sampling_points 3 Number of raw data points per FWHM of the peak 2:∞
++++++contaminants
file examples/simulation/contaminants.csv Contaminants file with sum formula and absolute RT interval. See 'OpenMS/examples/simulation/contaminants.txt' for details
++++++variation Random components that simulate biological and technical variations of the simulated data
+++++++mz Shifts in mass to charge dimension of the simulated signals
error_mean 0.0 Average systematic m/z error (in Da)
error_stddev 0.0 Standard deviation for m/z errors. Set to 0 to disable simulation of m/z errors
+++++++intensity Variations in intensity to model randomness in feature intensity
scale 100.0 Constant scale factor of the feature intensity. Set to 1.0 to get the real intensity values provided in the FASTA file 0.0:∞
scale_stddev 0.0 Standard deviation of peak intensity (relative to the scaled peak height). Set to 0 to get simple rescaled intensities 0.0:∞
++++++noise Parameters modeling noise in mass spectrometry measurements
+++++++shot Parameters of Poisson and Exponential for shot noise modeling (set :rate OR :mean = 0 to disable)
rate 0.0 Poisson rate of shot noise per unit m/z (random peaks in m/z, where the number of peaks per unit m/z follows a Poisson distribution). Set this to 0 to disable simulation of shot noise 0.0:∞
intensity-mean 1.0 Shot noise intensity mean (exponentially distributed with given mean)
+++++++white Parameters of Gaussian distribution for white noise modeling (set :mean AND :stddev = 0 to disable). No new peaks are generated; only intensity of existing ones is changed
mean 0.0 Mean value of white noise (Gaussian) being added to each *measured* signal intensity
stddev 0.0 Standard deviation of white noise being added to each *measured* signal intensity
+++++++detector Parameters of Gaussian distribution for detector noise modeling (set :mean AND :stddev = 0 to disable). If enabled, ALL possible m/z positions (up to sampling frequency of detector) will receive an intensity increase/decrease according to the specified Gaussian intensity distribution (similar to a noisy baseline)
mean 0.0 Mean intensity value of the detector noise (Gaussian distribution)
stddev 0.0 Standard deviation of the detector noise (Gaussian distribution)
+++++RawTandemSignal
status disabled Create Tandem-MS scans?disabled,precursor,MS^E
tandem_mode 0 Algorithm to generate the tandem-MS spectra. 0 - fixed intensities, 1 - SVC prediction (abundant/missing), 2 - SVR prediction of peak intensity
0:2
svm_model_set_file examples/simulation/SvmModelSet.model File containing the filenames of SVM Models for different charge variants
++++++Precursor
ms2_spectra_per_rt_bin 5 Number of allowed MS/MS spectra in a retention time bin.1:∞
min_mz_peak_distance 2.0 The minimal distance (in Th) between two peaks for concurrent selection for fragmentation. Also used to define the m/z width of an exclusion window (distance +/- from m/z of precursor). If you set this lower than the isotopic envelope of a peptide, you might get multiple fragment spectra pointing to the same precursor.1.0e-04:∞
mz_isolation_window 2.0 All peaks within a mass window (in Th) of a selected peak are also selected for fragmentation.0.0:∞
exclude_overlapping_peaks false If true, overlapping or nearby peaks (within 'min_mz_peak_distance') are excluded for selection.true,false
charge_filter[2, 3] Charges considered for MS2 fragmentation.1:5
+++++++Exclusion
use_dynamic_exclusion false If true dynamic exclusion is applied.true,false
exclusion_time 100.0 The time (in seconds) a feature is excluded.0.0:∞
+++++++ProteinBasedInclusion
max_list_size 1000 The maximal number of precursors in the inclusion list.1:∞
++++++++rt
min_rt 960.0 Minimal rt in seconds.0.0:∞
max_rt 3840.0 Maximal rt in seconds.0.0:∞
rt_step_size 30.0 rt step size in seconds.1.0:∞
rt_window_size 100 rt window size in seconds.1:∞
++++++++thresholds
min_protein_id_probability 0.95 Minimal protein probability for a protein to be considered identified.0.0:1.0
min_pt_weight 0.5 Minimal pt weight of a precursor 0.0:1.0
min_mz 500.0 Minimal mz to be considered in protein based LP formulation.0.0:∞
max_mz 5000.0 Minimal mz to be considered in protein based LP formulation.0.0:∞
use_peptide_rule false Use peptide rule instead of minimal protein id probability true,false
min_peptide_ids 2 If use_peptide_rule is true, this parameter sets the minimal number of peptide ids for a protein id 1:∞
min_peptide_probability 0.95 If use_peptide_rule is true, this parameter sets the minimal probability for a peptide to be safely identified 0.0:1.0
++++++MS_E
add_single_spectra false If true, the MS2 spectra for each peptide signal are included in the output (might be a lot). They will have a meta value 'MSE_DebugSpectrum' attached, so they can be filtered out. Native MS_E spectra will have 'MSE_Spectrum' instead.true,false
++++++TandemSim
+++++++Simple
isotope_model none Model to use for isotopic peaks ('none' means no isotopic peaks are added, 'coarse' adds isotopic peaks in unit mass distance, 'fine' uses the hyperfine isotopic generator to add accurate isotopic peaks. Note that adding isotopic peaks is very slow.none,coarse,fine
max_isotope 2 Defines the maximal isotopic peak which is added if 'isotope_model' is 'coarse'
max_isotope_probability 0.05 Defines the maximal isotopic probability to cover if 'isotope_model' is 'fine'
add_metainfo false Adds the type of peaks as metainfo to the peaks, like y8+, [M-H2O+2H]++true,false
add_losses false Adds common losses to those ion expect to have them, only water and ammonia loss is considered true,false
sort_by_position true Sort output by position true,false
add_precursor_peaks false Adds peaks of the unfragmented precursor ion to the spectrum true,false
add_all_precursor_charges false Adds precursor peaks with all charges in the given range true,false
add_abundant_immonium_ions false Add most abundant immonium ions true,false
add_first_prefix_ion false If set to true e.g. b1 ions are added true,false
add_y_ions true Add peaks of y-ions to the spectrum true,false
add_b_ions true Add peaks of b-ions to the spectrum true,false
add_a_ions false Add peaks of a-ions to the spectrum true,false
add_c_ions false Add peaks of c-ions to the spectrum true,false
add_x_ions false Add peaks of x-ions to the spectrum true,false
add_z_ions false Add peaks of z-ions to the spectrum true,false
y_intensity 1.0 Intensity of the y-ions
b_intensity 1.0 Intensity of the b-ions
a_intensity 1.0 Intensity of the a-ions
c_intensity 1.0 Intensity of the c-ions
x_intensity 1.0 Intensity of the x-ions
z_intensity 1.0 Intensity of the z-ions
relative_loss_intensity 0.1 Intensity of loss ions, in relation to the intact ion intensity
precursor_intensity 1.0 Intensity of the precursor peak
precursor_H2O_intensity 1.0 Intensity of the H2O loss peak of the precursor
precursor_NH3_intensity 1.0 Intensity of the NH3 loss peak of the precursor
+++++++SVM
add_isotopes false If set to 1 isotope peaks of the product ion peaks are added true,false
max_isotope 2 Defines the maximal isotopic peak which is added, add_isotopes must be set to 1
add_metainfo false Adds the type of peaks as metainfo to the peaks, like y8+, [M-H2O+2H]++true,false
add_first_prefix_ion false If set to true e.g. b1 ions are added true,false
hide_y_ions false Add peaks of y-ions to the spectrum true,false
hide_y2_ions false Add peaks of y-ions to the spectrum true,false
hide_b_ions false Add peaks of b-ions to the spectrum true,false
hide_b2_ions false Add peaks of b-ions to the spectrum true,false
hide_a_ions false Add peaks of a-ions to the spectrum true,false
hide_c_ions false Add peaks of c-ions to the spectrum true,false
hide_x_ions false Add peaks of x-ions to the spectrum true,false
hide_z_ions false Add peaks of z-ions to the spectrum true,false
hide_losses false Adds common losses to those ion expect to have them, only water and ammonia loss is considered true,false
y_intensity 1.0 Intensity of the y-ions
b_intensity 1.0 Intensity of the b-ions
a_intensity 1.0 Intensity of the a-ions
c_intensity 1.0 Intensity of the c-ions
x_intensity 1.0 Intensity of the x-ions
z_intensity 1.0 Intensity of the z-ions
relative_loss_intensity 0.1 Intensity of loss ions, in relation to the intact ion intensity
+++++Global
ionization_type ESI Type of Ionization (MALDI or ESI)MALDI,ESI
+++++Labeling
type labelfree Select the labeling type you want for your experiment ICPL,SILAC,itraq,labelfree,o18
++++++ICPL ICPL labeling on MS1 level of lysines and n-term (on protein or peptide level) with either two or three channels.
ICPL_fixed_rtshift 0.0 Fixed retention time shift between labeled pairs. If set to 0.0 only the retention times, computed by the RT model step are used.
label_proteins true Enables protein-labeling. (select 'false' if you only need peptide-labeling)true,false
ICPL_light_channel_label UniMod:365 UniMod Id of the light channel ICPL label.
ICPL_medium_channel_label UniMod:687 UniMod Id of the medium channel ICPL label.
ICPL_heavy_channel_label UniMod:364 UniMod Id of the heavy channel ICPL label.
++++++SILAC SILAC labeling on MS1 level with up to 3 channels and custom modifications.
fixed_rtshift 1.0e-04 Fixed retention time shift between labeled peptides. If set to 0.0 only the retention times computed by the RT model step are used.0.0:∞
+++++++medium_channel Modifications for the medium SILAC channel.
modification_lysine UniMod:481 Modification of Lysine in the medium SILAC channel
modification_arginine UniMod:188 Modification of Arginine in the medium SILAC channel
+++++++heavy_channel Modifications for the heavy SILAC channel. If you want to use only 2 channels, just leave the Labels as they are and provide only 2 input files.
modification_lysine UniMod:259 Modification of Lysine in the heavy SILAC channel. If left empty, two channelSILAC is assumed.
modification_arginine UniMod:267 Modification of Arginine in the heavy SILAC channel. If left empty, two-channel SILAC is assumed.
++++++itraq iTRAQ labeling on MS2 level with up to 4 (4plex) or 8 (8plex) channels.
iTRAQ 4plex 4plex or 8plex iTRAQ?4plex,8plex
reporter_mass_shift 0.1 Allowed shift (uniformly distributed - left to right) in Da from the expected position (of e.g. 114.1, 115.1)0.0:0.5
channel_active_4plex[114:myReference] Four-plex only: Each channel that was used in the experiment and its description (114-117) in format :, e.g. "114:myref","115:liver".
channel_active_8plex[113:myReference] Eight-plex only: Each channel that was used in the experiment and its description (113-121) in format :, e.g. "113:myref","115:liver","118:lung".
isotope_correction_values_4plex[114:0.0/1.0/5.9/0.2, 115:0.0/2.0/5.6/0.1, 116:0.0/3.0/4.5/0.1, 117:0.1/4.0/3.5/0.1] override default values (see Documentation); use the following format: :<-2Da>/<-1Da>/<+1Da>/<+2Da> ; e.g. '114:0/0.3/4/0' , '116:0.1/0.3/3/0.2'
isotope_correction_values_8plex[113:0.0/0.0/6.89/0.22, 114:0.0/0.94/5.9/0.16, 115:0.0/1.88/4.9/0.1, 116:0.0/2.82/3.9/0.07, 117:0.06/3.77/2.99/0.0, 118:0.09/4.71/1.88/0.0, 119:0.14/5.66/0.87/0.0, 121:0.27/7.44/0.18/0.0] override default values (see Documentation); use the following format: :<-2Da>/<-1Da>/<+1Da>/<+2Da> ; e.g. '113:0/0.3/4/0' , '116:0.1/0.3/3/0.2'
Y_contamination 0.3 Efficiency of labeling tyrosine ('Y') residues. 0=off, 1=full labeling 0.0:1.0
++++++o18 18O labeling on MS1 level with 2 channels, requiring trypsin digestion.
labeling_efficiency 1.0 Describes the distribution of the labeled peptide over the different states (unlabeled, mono- and di-labeled)0.0:1.0
++++RandomNumberGenerators Parameters for generating the random aspects (e.g. noise) in the simulated data. The generation is separated into two parts, the technical part, like noise in the raw signal, and the biological part, like systematic deviations in the predicted retention times
biological random Controls the 'biological' randomness of the generated data (e.g. systematic effects like deviations in RT). If set to 'random' each experiment will look different. If set to 'reproducible' each experiment will have the same outcome (given that the input data is the same)reproducible,random
technical random Controls the 'technical' randomness of the generated data (e.g. noise in the raw signal). If set to 'random' each experiment will look different. If set to 'reproducible' each experiment will have the same outcome (given that the input data is the same)reproducible,random