Define where the pipeline should find input data and save output data.

URI/path to an SDRF file OR globbing pattern for URIs/paths of mzML or Thermo RAW files

required
type: string

The output directory where the results will be saved.

type: string
default: ./results

Email address for completion summary.

type: string
pattern: ^([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})$

Less common options for the pipeline, typically set in a config file.

Display help text.

hidden
type: boolean

Method used to save pipeline results to output directory.

hidden
type: string

Workflow name.

hidden
type: string

Email address for completion summary, only when pipeline fails.

hidden
type: string
pattern: ^([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})$

Send plain-text email instead of HTML.

hidden
type: boolean

File size limit when attaching QC reports to summary emails.

hidden
type: string
default: 25 MB

Do not use coloured log outputs.

hidden
type: boolean

Directory to keep pipeline Nextflow logs and reports.

hidden
type: string
default: ${params.outdir}/pipeline_info

Set the top limit for requested resources for any single job.

Maximum number of CPUs that can be requested for any single job.

hidden
type: integer
default: 16

Maximum amount of memory that can be requested for any single job.

hidden
type: string
default: 128.GB

Maximum amount of time that can be requested for any single job.

hidden
type: string
default: 240.h

Parameters used to describe centralised config profiles. These should not be edited.

Git commit id for Institutional configs.

hidden
type: string
default: master

Base directory for Institutional configs.

hidden
type: string
default: https://raw.githubusercontent.com/nf-core/configs/master

Institutional configs hostname.

hidden
type: string

Institutional config description.

hidden
type: string

Institutional config contact information.

hidden
type: string

Institutional config URL link.

hidden
type: string

In case your input was an SDRF files, the following optional parameters can be set.

Root folder in which the spectrum files specified in the SDRF are searched

type: string

Overwrite the file type/extension of the filename as specified in the SDRF

type: string

In case your input was a globbing pattern to spectrum files in Thermo RAW or mzML format you can specify a manual OpenMS-style experimental design file here.

A tab-separated experimental design file in OpenMS’ own format (TODO link). All input files need to be present as a row with exactly the same names. If no design is given, unrelated, unfractionated runs are assumed.

type: string

Settings that relate to the mandatory protein database and the optional generation of decoy entries.

The fasta protein database used during database search.

required
type: string

Generate and append decoys to the given protein database

type: boolean

Pre- or suffix of decoy proteins in their accession

type: string
default: DECOY_

Location of the decoy marker string in the fasta accession. Before (prefix) or after (suffix)

type: string
default: prefix

In case you start from profile mode mzMLs or the internal preprocessing during conversion with the ThermoRawFileParser fails (e.g. due to new instrument types), preprocessing has to be performed with OpenMS. Use this section to configure.

Activate OpenMS-internal peak picking

type: boolean

Perform peakpicking in memory

type: boolean

Which MS levels to pick as comma separated list. Leave empty for auto-detection.

type: string

A comma separated list of search engines. Valid: comet, msgf

type: string
default: comet

The enzyme to be used for in-silico digestion, in ‘OpenMS format’

type: string
default: Trypsin

Specify the amount of termini matching the enzyme cutting rules for a peptide to be considered. Valid values are fully (default), semi, or none

type: string

Specify the maximum number of allowed missed enzyme cleavages in a peptide. The parameter is not applied if unspecific cleavage is specified as enzyme.

type: integer
default: 2

Precursor mass tolerance used for database search. For High-Resolution instruments a precursor mass tolerance value of 5 ppm is recommended (i.e. 5). See also --precursor_mass_tolerance_unit.

type: integer
default: 5

Precursor mass tolerance unit used for database search. Possible values are ‘ppm’ (default) and ‘Da’.

type: string

Fragment mass tolerance used for database search. The default of 0.03 Da is for high-resolution instruments.

type: number
default: 0.03

Fragment mass tolerance unit used for database search. Possible values are ‘ppm’ (default) and ‘Da’.

type: string

A comma-separated list of fixed modifications with their Unimod name to be searched during database search

type: string
default: Carbamidomethyl (C)

A comma-separated list of variable modifications with their Unimod name to be searched during database search

type: string
default: Oxidation (M)

The fragmentation method used during tandem MS. (MS/MS or MS2).

hidden
type: string
default: HCD

Comma-separated range of integers with allowed isotope peak errors for precursor tolerance (MS-GF+ parameter ‘-ti’). E.g. -1,2

type: string
default: 0,1

Type of instrument that generated the data. ‘low_res’ or ‘high_res’ (default; refers to LCQ and LTQ instruments)

type: string
default: high_res

MSGF only: Labeling or enrichment protocol used, if any. Default: automatic

type: string
default: automatic

Minimum precursor ion charge. Omit the ’+’

type: integer
default: 2

Maximum precursor ion charge. Omit the ’+’

type: integer
default: 4

Minimum peptide length to consider (works with MSGF and in newer Comet versions)

type: integer
default: 6

Maximum peptide length to consider (works with MSGF and in newer Comet versions)

type: integer
default: 40

Specify the maximum number of top peptide candidates per spectrum to be reported by the search engine. Default: 1

type: integer
default: 1

Maximum number of modifications per peptide. If this value is large, the search may take very long.

type: integer
default: 3

Debug level when running the database search. Logs become more verbose and at ‘>5’ temporary files are kept.

type: integer

Settings for calculating a localization probability with LucXor for modifications with multiple candidate amino acids in a peptide.

Turn the mechanism on.

type: boolean

Which variable modifications to use for scoring their localization.

type: string
default: Phospho (S),Phospho (T),Phospho (Y)

List of neutral losses to consider for mod. localization.

hidden
type: string

How much to add to an amino acid to make it a decoy for mod. localization.

hidden
type: number

List of neutral losses to consider for mod. localization from an internally generated decoy sequence.

hidden
type: string

Debug level for Luciphor step. Increase for verbose logging and keeping temp files.

hidden
type: integer

Do not fail if there are some unmatched peptides. Only activate as last resort, if you know that the rest of your settings are fine!

type: string

Should isoleucine and leucine be treated interchangeably when mapping search engine hits to the database? Default: true

type: string

Choose between different rescoring/posterior probability calculation methods and set them up.

How to calculate posterior probabilities for PSMs:

  • ‘percolator’ = Re-score based on PSM-feature-based SVM and transform distance to hyperplane for posteriors
  • ‘fit_distributions’ = Fit positive and negative distributions to scores (similar to PeptideProphet)
type: string

FDR cutoff on PSM level (or potential peptide level; see Percolator options) before going into feature finding, map alignment and inference.

type: number
default: 0.1

Debug level when running the re-scoring. Logs become more verbose and at ‘>5’ temporary files are kept.

type: integer

In the following you can find help for the Percolator specific options that are only used if --posterior_probabilities was set to ‘percolator’. Note that there are currently some restrictions to the original options of Percolator:

  • no Percolator protein FDR possible (currently OpenMS’ FDR is used on protein level)
  • no support for separate target and decoy databases (i.e. no min-max q-value calculation or target-decoy competition strategy)
  • no support for combined or experiment-wide peptide re-scoring. Currently search results per input file are submitted to Percolator independently.

Calculate FDR on PSM (‘psm-level-fdrs’) or peptide level (‘peptide-level-fdrs’)?

type: string

The FDR cutoff to be used during training of the SVM.

type: number
default: 0.05

The FDR cutoff to be used during testing of the SVM.

type: number
default: 0.05

Only train an SVM on a subset of PSMs, and use the resulting score vector to evaluate the other PSMs. Recommended when analyzing huge numbers (>1 million) of PSMs. When set to 0, all PSMs are used for training as normal. This is a runtime vs. discriminability tradeoff. Default: 300,000

type: integer
default: 300000

Retention time features are calculated as in Klammer et al. instead of with Elude. Default: false

hidden
type: boolean

Use additional features whose values are learnt by correct entries. See help text. Default: 0 = none

type: integer

Use this instead of Percolator if there are problems with Percolator (e.g. due to bad separation) or for performance

How to handle outliers during fitting:

  • ignore_iqr_outliers (default): ignore outliers outside of 3*IQR from Q1/Q3 for fitting
  • set_iqr_to_closest_valid: set IQR-based outliers to the last valid value for fitting
  • ignore_extreme_percentiles: ignore everything outside 99th and 1st percentile (also removes equal values like potential censored max values in XTandem)
  • none: do nothing
type: string

How to combine the probabilities from the single search engines: best, combine using a sequence similarity-matrix (PEPMatrix), combine using shared ion count of peptides (PEPIons). See help for further info.

type: string

Only use the top N hits per search engine and spectrum for combination. Default: 0 = all

type: integer

A threshold for the ratio of occurence/similarity scores of a peptide in other runs, to be reported. See help.

type: integer

To group proteins, calculate scores on the protein (group) level and to potentially modify associations from peptides to proteins.

The inference method to use. ‘aggregation’ (default) or ‘bayesian’.

type: string

The experiment-wide protein (group)-level FDR cutoff. Default: 0.05

type: number
default: 0.05

Quantify proteins based on:

  • ‘unique_peptides’ = use peptides mapping to single proteins or a group of indistinguishable proteins (according to the set of experimentally identified peptides)
  • ‘strictly_unique_peptides’ = use peptides mapping to a unique single protein only
  • ‘shared_peptides’ = use shared peptides, too, but only greedily for its best group (by inference score)
type: string

Choose between feature-based quantification based on integrated MS1 signals (‘feature_intensity’; default) or spectral counting of PSMs (‘spectral_counting’). WARNING: ‘spectral_counting’ is not compatible with our MSstats step yet. MSstats will therefore be disabled automatically with that choice.

type: string

Recalibrates masses based on precursor mass deviations to correct for instrument biases. (default: ‘false’)

type: boolean

Tries a targeted requantification in files where an ID is missing, based on aggregate properties (i.e. RT) of the features in other aligned files (e.g. ‘mean’ of RT). (WARNING: increased memory consumption and runtime). ‘false’ turns this feature off. (default: ‘false’)

type: string

Only looks for quantifiable features at locations with an identified spectrum. Set to false to include unidentified features so they can be linked and matched to identified ones (= match between runs). (default: ‘true’)

type: boolean
default: true

Debug level when running the re-scoring. Logs become more verbose and at ‘>666’ potentially very large temporary files are kept.

type: integer

Skip MSstats for statistical post-processing?

type: boolean

Instead of all pairwise contrasts (default), uses the given condition name/number (corresponding to your experimental design) as a reference and creates pairwise contrasts against it. (TODO not yet fully implemented)

type: string

Allows full control over contrasts by specifying a set of contrasts in a semicolon seperated list of R-compatible contrasts with the condition names/numbers as variables (e.g. 1-2;1-3;2-3). Overwrites ‘—ref_condition’ (TODO not yet fully implemented)

type: string

Enable generation of quality control report by PTXQC? default: ‘false’ since it is still unstable

type: boolean

Specify a yaml file for the report layout (see PTXQC documentation) (TODO not yet fully implemented)

type: string