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Peptide Query Parameter Generation

PQP Generation for OpenSWATH

After importing transitions lists from an upstream workflow (e.g. :doc:`tpp`, :doc:`skyline` or :doc:`generic`), the transitions can then be optimized using a set of heuristic rules [1]:

OpenSwathAssayGenerator -in transitionlist.TraML \
-out transitionlist_optimized.TraML \
-swath_windows_file swath64.txt \

Please note that the SWATH windows file should be of the following format (tab-separated), including header:

lower_offset upper_offset
400 425
424 450

If necessary, the rules for transition selection can be modified with the following parameters:

OpenSwathAssayGenerator <other parameters>
-min_transitions 6 \
-max_transitions 6 \
-allowed_fragment_types b,y \
-allowed_fragment_charges 1,2,3,4 \
-enable_detection_specific_losses \
-enable_detection_unspecific_losses \
-precursor_mz_threshold 0.025 \
-precursor_lower_mz_limit 400 \
-precursor_upper_mz_limit 1200 \
-product_mz_threshold 0.025 \
-product_lower_mz_limit 350 \
-product_upper_mz_limit 2000 \

PQP Generation for IPF

If IPF scoring [2] should be conducted, the following parameters should be considered in addition to the others above:

OpenSwathAssayGenerator <other parameters>
-enable_ipf \
-unimod_file unimod_phospho.xml \

Unimod contains descriptions of more than 1400 post-translational modifications and represents the standard database. However, many modification types are annotated with residue modifiabilites that go beyond the canonical set (e.g. phosphorylation (S,T,Y,D,H,C,R,K) instead of (S,T,Y)).

For the purpose of site-localization, it is thus very important to provide a modified (restricted) Unimod file to OpenSwathAssayGenerator. This file can be created by editing the file unimod.xml to only the desired modifications and residue modifiabilites. We provide an example for Phosphorylation (S,T,Y), Carbamidomethyl (C), Oxidation (M) and SILAC (R, K). Please note that also usually fixed PTMs like Carbamidomethyl and Oxidation need to be set.

The generation of identification transitions can be adjusted if necessary by the following parameters:

OpenSwathAssayGenerator <other parameters>
-enable_ipf \
-unimod_file unimod_phospho.xml \
-max_num_alternative_localizations 10000 \
-disable_identification_ms2_precursors \
-disable_identification_specific_losses \
-enable_identification_unspecific_losses \
-enable_swath_specifity \

OpenSwathAssayGenerator excludes peptides that can have too many combinations of alternative site-localization (track the process by setting -debug 10). If 10000 alternative peptidoforms are too few, consider increasing this parameter.

By default, unfragmented precursors are extracted from the SWATH maps and used for scoring by IPF, this can optionally be disabled (-disable_identification_ms2_precursors). Specific losses (e.g. for Phosphorylation) are used by default and improve specificity; unspecific losses are not recommended to use.

In scenarios with extremely small precursor isolation windows (e.g. < 1 Th), -enable_swath_specificity can be used to skip the precursor inference step of IPF. This is not recommended in general.

Decoy Generation

Decoys can then be appended using OpenSwathDecoyGenerator:

OpenSwathDecoyGenerator -in transitionlist_optimized.TraML \
-out transitionlist_optimized_decoys.TraML \


If you used non-default parameters in OpenSwathAssayGenerator (i.e. -product_mz_threshold, -allowed_fragment_types, -allowed_fragment_charges, -enable_detection_specific_losses or -enable_detection_unspecific_losses), make sure to also specify them for OpenSwathDecoyGenerator. The flag --helphelp will show a list of all options.

You can then convert the TraML to a PQP file:

TargetedFileConverter -in transitionlist_optimized_decoys.TraML \
-out transitionlist_optimized_decoys.PQP \

This processed spectral library (including decoys) is the input for :doc:`openswath`.


[1]Schubert OT, Gillet LC, Collins BC, Navarro P, Rosenberger G, Wolski WE, Lam H, Amodei D, Mallick P, MacLean B, Aebersold R. Building high-quality assay libraries for targeted analysis of SWATH MS data. Nat Protoc. 2015 Mar;10(3):426-41. doi: 10.1038/nprot.2015.015. Epub 2015 Feb 12. PMID: 25675208
[2]Rosenberger G, Liu Y, Röst HL, Ludwig C, Buil A, Bensimon A, Soste M, Spector TD, Dermitzakis ET, Collins BC, Malmström L, Aebersold R. Inference and quantification of peptidoforms in large sample cohorts by SWATH-MS. Nat Biotechnol. 2017 Aug;35(8):781-788. doi: 10.1038/nbt.3908. Epub 2017 Jun 12. PMID: 28604659