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This document lists every pipeline parameter organised by category. Default values come from nextflow.config; types and constraints come from nextflow_schema.json.
1. Input/Output Options
Parameter
Type
Default
Description
--input
string (file-path)
required
URI/path to an SDRF file with .sdrf, .tsv, or .csv extension. Parameters such as enzyme, fixed modifications, and acquisition method are read from the SDRF.
--database
string (file-path)
required
Path to a FASTA protein database. Must not contain decoys for DIA data.
--outdir
string (directory-path)
./results
The output directory where results will be saved.
--publish_dir_mode
string
copy
Method used to save pipeline results. One of: symlink, rellink, link, copy, copyNoFollow, move.
--root_folder
string
null
Root folder in which spectrum files specified in the SDRF are searched. Used when you have a local copy of the experiment.
--local_input_type
string
mzML
Overwrite the file type/extension of filenames in the SDRF when using --root_folder. One of: mzML, raw, d, dia. Compressed variants (.gz, .tar, .tar.gz, .zip) are supported for mzML, raw, and d.
--email
string
null
Email address for completion summary.
2. SDRF Validation
Parameter
Type
Default
Description
--use_ols_cache_only
boolean
true
Use only the cached Ontology Lookup Service (OLS) for ontology term validation. Set to false to allow network requests.
3. File Preparation (Spectrum Preprocessing)
Parameter
Type
Default
Description
--reindex_mzml
boolean
true
Force re-indexing of input mzML files at the start of the pipeline for safety.
--mzml_statistics
boolean
false
Compute MS1/MS2 statistics from mzML files. Generates *_ms_info.parquet files for QC. Bruker .d files are always skipped.
--mzml_features
boolean
false
Compute MS1-level features during the mzML statistics step. Only available for mzML files.
4. Search Parameters
Parameter
Type
Default
Description
--met_excision
boolean
true
Account for N-terminal methionine excision during database search.
--allowed_missed_cleavages
integer
2
Maximum number of allowed missed enzyme cleavages per peptide.
--precursor_mass_tolerance
integer
5
Precursor mass tolerance for database search (see --precursor_mass_tolerance_unit). Can be overridden; falls back to SDRF value.
--precursor_mass_tolerance_unit
string
ppm
Precursor mass tolerance unit. One of: ppm, Da.
--fragment_mass_tolerance
number
0.03
Fragment mass tolerance for database search (see --fragment_mass_tolerance_unit).
--fragment_mass_tolerance_unit
string
Da
Fragment mass tolerance unit. One of: ppm, Da.
--variable_mods
string
Oxidation (M)
Comma-separated variable modifications in Unimod format (e.g. Oxidation (M),Carbamidomethyl (C)). Can be overridden; falls back to SDRF.
--min_precursor_charge
integer
2
Minimum precursor ion charge.
--max_precursor_charge
integer
4
Maximum precursor ion charge.
--min_peptide_length
integer
6
Minimum peptide length to consider.
--max_peptide_length
integer
40
Maximum peptide length to consider.
--max_mods
integer
3
Maximum number of variable modifications per peptide.
--min_pr_mz
number
400
Minimum precursor m/z for in-silico library generation or library-free search.
--max_pr_mz
number
2400
Maximum precursor m/z for in-silico library generation or library-free search.
--min_fr_mz
number
100
Minimum fragment m/z for in-silico library generation or library-free search.
--max_fr_mz
number
1800
Maximum fragment m/z for in-silico library generation or library-free search.
5. DIA-NN General
Parameter
Type
Default
Description
--diann_version
string
1.8.1
DIA-NN version used by the workflow. Controls version-dependent flags (e.g. --monitor-mod for 1.8.x). See DIA-NN Version Selection.
--debug_level
integer
3
DIA-NN debug/verbosity level (0-4). Higher values produce more verbose logs.
--speclib
string
null
Path to an external spectral library. If provided, the in-silico library generation step is skipped.
--extra_args
string
null
Extra arguments appended to all DIA-NN steps. Flags incompatible with a step are automatically stripped with a warning. See Passing Extra Arguments to DIA-NN.
--dda
boolean
false
Explicitly enable DDA mode. Normally auto-detected from the SDRF comment[proteomics data acquisition method] column. Use this flag only when the SDRF lacks the acquisition method. Requires DIA-NN >= 2.3.2.
Enable --export-quant for fragment-level parquet data export. Requires DIA-NN >= 2.0.
--site_ms1_quant
boolean
false
Enable --site-ms1-quant to use MS1 apex intensities for PTM site quantification. Requires DIA-NN >= 2.0.
--aa_eq
boolean
false
Treat I&L, Q&E, N&D as equivalent amino acids during reannotation. Essential for entrapment FDR benchmarks. Maps to --aa-eq.
DIA-NN 2.5.0 flags (via --extra_args)
The following DIA-NN 2.5.0 flags are not exposed as pipeline parameters but can be passed via --extra_args. See Fine-Tuning Deep Learning Models for the complete workflow.
Fine-tuned retention time prediction model (.pt PyTorch file).
--fr-model <file>
Fine-tuned fragment ion prediction model (.pt file). Quality-sensitive — verify vs base model.
--im-model <file>
Fine-tuned ion mobility prediction model (.pt file).
--tune-lib <file>
Spectral library for fine-tuning (.parquet). Requires --tune-rt and/or --tune-im.
--tune-rt
Fine-tune the RT deep learning predictor. Requires --tune-lib.
--tune-im
Fine-tune the IM deep learning predictor. Requires --tune-lib.
--tune-fr
Fine-tune the fragmentation predictor. Requires --tune-lib. Use with caution.
--tune-lr <X>
Fine-tuning learning rate (default: 0.0005).
--tune-restrict-layers
Keep RNN layer weights fixed during fine-tuning (except cysteine embeddings).
--tune-level <N>
Limit fine-tuning to a specific model distillation level (0, 1, or 2).
Note:--parent and --aa-eq are blocked from --extra_args — they are managed as pipeline parameters (--aa_eq). --parent is container-managed and overriding it would break model discovery.
6. Mass Accuracy & Calibration
Parameter
Type
Default
Description
--mass_acc_automatic
boolean
true
Automatically determine MS2 mass accuracy. When true, --mass_acc_ms2 is ignored during preliminary analysis.
--mass_acc_ms1
number
15
MS1 mass accuracy in ppm. Overrides automatic calibration when --mass_acc_automatic false. Maps to DIA-NN --mass-acc-ms1.
--mass_acc_ms2
number
15
MS2 mass accuracy in ppm. Overrides automatic calibration when --mass_acc_automatic false. Maps to DIA-NN --mass-acc.
--scan_window
integer
8
Scan window radius. Should approximate the average number of data points per peak.
--scan_window_automatic
boolean
true
Automatically determine the scan window. When true, --scan_window is ignored.
--quick_mass_acc
boolean
true
Use a fast heuristic algorithm for mass accuracy calibration instead of ID-number optimisation.
Reuse existing .quant files if available (--use-quant).
--quantums
boolean
false
Enable QuantUMS quantification (requires DIA-NN >= 1.9.2). When false, the pipeline passes --direct-quant to use legacy quantification (only for DIA-NN >= 1.9.2; silently skipped for 1.8.x where direct quant is the only mode).
--quantums_train_runs
string
null
Run index range for QuantUMS training (e.g. 0:5). Maps to --quant-train-runs. Requires DIA-NN >= 1.9.2.
--quantums_sel_runs
integer
null
Number of automatically selected runs for QuantUMS training. Must be >= 6. Maps to --quant-sel-runs. Requires DIA-NN >= 1.9.2.
--quantums_params
string
null
Pre-calculated QuantUMS parameters. Maps to --quant-params. Requires DIA-NN >= 1.9.2.
12. DDA Mode
Parameter
Type
Default
Description
--dda
boolean
false
Explicitly enable DDA mode when SDRF lacks the acquisition method column. Normally DDA is auto-detected from the SDRF comment[proteomics data acquisition method]. Requires DIA-NN >= 2.3.2 (use -profile diann_v2_3_2). Beta feature.
Note: DDA mode is auto-detected from the SDRF when the comment[proteomics data acquisition method]
column contains data-dependent acquisition. The --dda flag is only needed as a
fallback when the SDRF does not include this column. DDA requires DIA-NN >= 2.3.2
(-profile diann_v2_3_2).