OpenSWATH  is a proteomics software that allows analysis of LC-MS/MS DIA (data independent acquisition) data using the approach described by Gillet et al.  and implemented as part of OpenMS . The original SWATH-MS method uses 32 cycles to iterate through precursor ion windows from 400-426 Da to 1175-1201 Da and at each step acquire a complete, multiplexed fragment ion spectrum of all precursors present in that window. After 32 fragmentations (or 3.2 seconds), the cycle is restarted and the first window (400-426 Da) is fragmented again, thus delivering complete “snapshots” of all fragments of a specific window every 3.2 seconds.
The analysis approach described by Gillet et al. extracts ion traces of specific fragment ions from all MS2 spectra that have the same precursor isolation window, thus generating data that is very similar to SRM traces.
The OpenSwathWorkflow executable is currently the most efficient way of running
OpenSWATH   and it is available through OpenMS . An extended
tutorial describing a complete OpenSWATH analysis workflow using
OpenSwathWorkflow was recently published  and is also available from
bioRxiv with its
The OpenSwathWorkflow implements the OpenSWATH analysis workflow as described in  and provides a complete, integrated analysis tool without the need to run multiple tools consecutively.
It executes the following steps in order:
- Reading of the raw input file (provided as mzML, mzXML or sqMass) and RT normalization transition list
- Computing the retention time transformation using RT normalization peptides
- Reading of the transition list
- Extracting the specified transitions
- Scoring the peak groups in the extracted ion chromatograms (XIC)
- Reporting the peak groups and the chromatograms
Contact and Support¶
The input to OpenSwathWorkflow are provided using the following files:
inraw input file (provided as mzML, mzXML or sqMass)
trtransition list (spectral library)
tr_irtan optional transition file containing RT normalization coordinates
swath_windows_filean optional file specifying the analysis SWATH windows
Mass spectrometric data¶
The input file
in is generally a single
(converted from a raw vendor file format using ProteoWizard).
The spectral library
tr is a spectral library either in
.PQP format (where the
PQP format is recommended). Further information in generating these files can be found in the Generic Transition Lists section.
Retention time normalization¶
The retention time normalization peptides are provided using the optional
tr_irt in TraML format. We suggest to use the
iRTassays.TraML file provided in
the tutorial dataset, if the Biognosys iRT-kit was used during sample preparation.
If the iRT-kit was not used, it is highly recommended to use or generate a set of endogenous peptides for RT normalization. A recent publication  provides such a set of
CiRT peptides suitable for many eukaryotic samples. The TraML file from the supplementary information can be used as input for
tr_irt. Since not all
CiRT peptides might be found, the flag
RTNormalization:estimateBestPeptides should be set to improve initial filtering of poor signals. Further parameters for optimization can be found when invoking
OpenSwathWorkflow --helphelp under the
RTNormalization section. Those do not require adjustment for most common sample types and LC-MS/MS setups, but might be useful to tweak for specific scenarios.
SWATH windows definition¶
The SWATH windows themselves can either be read from the input files, but it is recommended to provide them explicitly in tab-delimited form. Note that there is a difference between the SWATH window acquisition scheme settings and the SWATH window analysis settings:
The acquisition settings tell the instrument how to acquire the data and how to filter the transitions (see section Peptide Query Parameter Generation).
The analysis settings on the other hand specify from which precursor isolation windows to extract the data. Note that the analysis windows should not have any overlap.
We suggest to use the
SWATHwindows_analysis.tsv file provided in the tutorial dataset for 32 windows of 25 Da each.
Caching of mass spectrometric data¶
Due to the large size of the files, OpenSwathWorkflow implements a caching
strategy where files are cached to disk and then read into memory
SWATH-by-SWATH. You can enable this by setting
cacheWorkingInMemory -tempDirectory /tmp where you would need to adjust the
temporary directory depending on your platform.
Other potentially useful options you may want to turn on are
The current parameters are optimized for 2 hour gradients on SCIEX 5600 /
6600 TripleTOF instruments with a peak width of around 30 seconds using iRT
peptides. If your chromatography differs, please consider adjusting
-Scoring:TransitionGroupPicker:min_peak_width to allow for smaller or larger
peaks and adjust the
-rt_extraction_window to use a different extraction
window for the retention time.
Mass spectrometric parameters¶
In m/z domain, consider adjusting
-mz_extraction_window to your instrument resolution, which can be in Th or
-ppm). In addition to using the iRT peptides for correction of
the retention time space, OpenSWATH can also use those peptides to correct the m/z space
with the option
-mz_correction_function quadratic_regression_delta_ppm. For
quantification, it can be beneficial to enable background subtraction using
-TransitionGroupPicker:background_subtraction original as described in the
software comparison paper .
MS1 and IPF parameters¶
Furthermore, if you wish to use MS1 information, use the
-use_ms1_traces flag, assuming that your input data contains an MS1 map in addition to the SWATH data. This is generally recommended. If you would like to enable IPF transition-level scoring and your spectral library was generated according to the IPF instructions, you should set the
Therefore, a full run of OpenSWATH may look like this:
OpenSwathWorkflow.exe -in data.mzML -tr library.tsv -tr_irt iRT_assays.TraML -swath_windows_file SWATHwindows_analysis.tsv -sort_swath_maps -batchSize 1000 -readOptions cacheWorkingInMemory -tempDirectory C:\Temp -use_ms1_traces -mz_extraction_window 50 -mz_extraction_window_unit ppm -mz_correction_function quadratic_regression_delta_ppm -TransitionGroupPicker:background_subtraction original -RTNormalization:alignmentMethod linear -Scoring:stop_report_after_feature 5 -out_tsv osw_output.tsv
If you encounter issues with peak picking, try to disable peak filtering by
-Scoring:TransitionGroupPicker:compute_peak_quality false which will
disable the filtering of peaks by chromatographic quality. Furthermore, you
can adjust the smoothing parameters for the peak picking, by adjusting
-Scoring:TransitionGroupPicker:PeakPickerMRM:sgolay_frame_length or using a
Gaussian smoothing based on your estimated peak width. Adjusting the signal
to noise threshold will make the peaks wider or smaller.
The OpenSwathWorkflow produces two types of output:
- identified peaks
- extracted chromatograms
the identified peaks can be stored in tsv format using
(recommended), in SQLite format using
-out_osw (experimental) or in a
featureXML format using
-out_features (not recommended).
the extracted chromatograms can be stored in mzML format using
.mzML extension. By default the produced mzML file will be numpress
compressed, but can be converted to regular mzML using the OpenMS
FileConverter. Alternatively, output can be written in
which is a SQLite-based format (experimental).
To learn OpenSWATH, we suggest to use the M. tuberculosis dataset published alongside the 2017 Methods Mol Biol. OpenSWATH tutorial  which is available from the PeptideAtlas raw data repository with accession number PASS00779.
The SWATH-MS Gold Standard and Streptococcus pyogenes data sets (used in the original 2014 Nature Biotechnoly publication) are available from the PeptideAtlas raw data repository with accession number PASS00289.
The Skyline results are available from Skyline Panorama Webserver.
Mycobacterium tuberculosis data¶
- 3 mzML instrument data files (centroided)
- 3 WIFF raw instrument data files
- Mtb assay library (for OpenMS 2.1)
- Mtb assay library (for older OpenMS)
- Swath windows file for analysis
- iRT assay file (TraML format)
SWATH-MS Gold Standard¶
- 90 mzXML instrument data files
- 90 WIFF raw instrument data files
- SGS TSV assay library
- SGS TraML assay library
- SGS OpenSWATH results
- SGS Skyline results on Panorama
- SGS manual results
- 4 mzXML instrument data files
- 4 WIFF raw instrument data files
- S. pyo TSV assay library
- S. pyo TraML assay library
- S. pyo OpenSWATH results
- S. pyo summary results
|||(1, 2, 3) Röst HL, Rosenberger G, Navarro P, Gillet L, Miladinović SM, Schubert OT, Wolski W, Collins BC, Malmström J, Malmström L, Aebersold R. OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data. Nat Biotechnol. 2014 Mar 10;32(3):219-23. doi: 10.1038/nbt.2841. PMID: 24727770|
|||(1, 2) Gillet LC, Navarro P, Tate S, Röst H, Selevsek N, Reiter L, Bonner R, Aebersold R. Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. Mol Cell Proteomics. 2012 Jun;11(6):O111.016717. Epub 2012 Jan 18. PMID: 22261725|
|||(1, 2) Röst HL, Sachsenberg T, Aiche S, Bielow C, Weisser H, Aicheler F, Andreotti S, Ehrlich HC, Gutenbrunner P, Kenar E, Liang X, Nahnsen S, Nilse L, Pfeuffer J, Rosenberger G, Rurik M, Schmitt U, Veit J, Walzer M, Wojnar D, Wolski WE, Schilling O, Choudhary JS, Malmström L, Aebersold R, Reinert K, Kohlbacher O. OpenMS: a flexible open-source software platform for mass spectrometry data analysis. Nat Methods. 2016 Aug 30;13(9):741-8. doi: 10.1038/nmeth.3959. PMID: 27575624|
|||(1, 2) Röst HL, Aebersold R, Schubert OT. Automated SWATH Data Analysis Using Targeted Extraction of Ion Chromatograms. Methods Mol Biol. 2017;1550:289-307. doi: 10.1007/978-1-4939-6747-6_20. PMID: 28188537. bioRxiv.|
|||Parker SJ, Rost H, Rosenberger G, Collins BC, Malmström L, Amodei D, Venkatraman V, Raedschelders K, Van Eyk JE, Aebersold R. Identification of a Set of Conserved Eukaryotic Internal Retention Time Standards for Data-independent Acquisition Mass Spectrometry. Mol Cell Proteomics. 2015 Oct;14(10):2800-13. doi: 10.1074/mcp.O114.042267. Epub 2015 Jul 21. PMID: 26199342|
|||Navarro P, Kuharev J, Gillet LC, Bernhardt OM, MacLean B, Röst HL, Tate SA, Tsou CC, Reiter L, Distler U, Rosenberger G, Perez-Riverol Y, Nesvizhskii AI, Aebersold R, Tenzer S. A multicenter study benchmarks software tools for label-free proteome quantification. Nat Biotechnol. 2016 Nov;34(11):1130-1136. doi: 10.1038/nbt.3685. Epub 2016 Oct 3.|