Analyzing DIA data
FragPipe can be downloaded here. Follow the instructions on that same Releases page to launch the program. See here for help configuring FragPipe.
FragPipe currently offers two workflows for DIA data:
1) DIA_SpecLib_Quant - takes DIA data (plus optional DDA data) as input, builds a spectral library using MSFragger-DIA, then quantifies with DIA-NN
2) DIA_DIA-Umpire_SpecLib_Quant - takes DIA data (plus optional DDA data) as input, DIA-Umpire generates pseudo-MS/MS spectra from the DIA files (instead of direct search with MSFragger-DIA), then MSFragger in DDA mode is used to search, followed by quantification with DIA-NN
Please note:
- DIA data acquired with overlapping/staggered windows must be converted to mzML using the ‘Demultiplex’ filter, see this page.
- To quantify from .raw files, Thermo MS File Reader must be installed, see the DIA-NN documentation for details.
- Any pseudo-MS/MS files from DIA-Umpire (
*_Q1.mzML,*_Q2.mzML,*_Q3.mzML) should be designated DDA data type on the Workflow tab. - If you already have a spectral library and want to quantify only, uncheck all steps except ‘Quantify with DIA-NN’ on the ‘Quant (DIA)’ tab, set the path to the spectral library, and run.
- Multiple spectral libraries can be generated in a single FragPipe run if multiple experiments are specified on the Workflow tab.
- If iRT peptides were spiked-in to the samples, change the ‘RT calibration’ option on the ‘Spec Lib’ tab to ‘iRT’. EasyPQP will use the ciRT option by default.
- diaPASEF data is not supported at this time.
- Skyline users may also choose to import interact-.pep.xml files into Skyline for spectral library building and further analysis of DIA experiments, see this tutorial.
The example dataset used here was downloaded from PXD011691. It includes 10 samples analyzed using DIA (10 mouse brain tissue, with UPS proteins spiked in at varying concentration). It also includes 6 DDA runs (pool of the same 10 brain tissues, with peptides fractionated into 6 fractions) collected for building a spectrum library. Download a subset of the dataset (‘speclib-raw.zip’, containing 2 DIA and 2 DDA files in mzML format plus a sequence database) from Dropbox to use for these demos.
Configure FragPipe
Python (with EasyPQP installed) is needed for spectral library generation. On the Config tab, check that a valid Python path is provided (Python version will be shown) and that EasyPQP is ‘Available’. If Python is installed but EasyPQP is missing, click the ‘Install/Upgrade EasyPQP’ button and wait a minute or so for installation. For help installing Python, see this page.
DIA_SpecLib_Quant
- In the Workflow tab, select the ‘DIA_SpecLib_Quant’ workflow from the dropdown menu and click ‘Load’.
- Load DIA (and optionally additional DDA) spectral files in mzML or raw format. You can use the ‘Add folder recursively’ button to browse for the unzipped ‘speclib-raw’ folder, which will load 2 DIA files and 2 DDA files. The data type of each file should be automatically detected by FragPipe, check that these assignments are correct.
- On the Database tab, use ‘Browse’ to select the FASTA sequence database file
2021-05-13-decoys-UPS-reviewed-contam-UP000000589.fasin the ‘speclib-raw’ folder. This is a mouse database with reviewed sequences, decoys, common contaminants, and iRT peptides. UPS protein sequences have been manually added.
- On the ‘Quant (DIA)’ tab, note that DIA-NN will be run unless unchecked. The spectral library generated by FragPipe will automatically be passed to DIA-NN for quantification of the DIA files provided.
- On the ‘Run’ tab, set the output directory and click ‘Run’. Example output from this workflow can be downloaded here.
DIA_DIA-Umpire_SpecLib_Quant
Follow the same steps as above to run the ‘DIA_DIA-Umpire_SpecLib_Quant’ workflow, which uses DIA-Umpire to generate pseudo-DDA spectra instead of MSFragger-DIA direct search of the DIA files. On the ‘Umpire’ tab, choose the appropriate settings:
- Change ‘Max Missed Scans’ to 2 if building a library from DIA data only (slower run time but higher identification sensitivity).
- Check ‘Remove Background’ if building a hybrid DDA+DIA library (see below) and if there are many DIA runs (fastest run time).
- Uncheck ‘Mass Defect Filter’ if DIA data is generated on modification-enriched peptides (e.g. phospho), or if you’re interested in extended PTM searches.
Please note that if DIA-Umpire fails or is interrupted, temporary files will cause issues if the process runs again. Make sure to delete any temporary files that are generated alongside the raw/mzML files before re-running FragPipe.
Example output from this workflow can be downloaded here.
Key References
Tsou CC, Avtonomov D, Larsen B, Tucholska M, Choi H, Gingras AC, Nesvizhskii AI. DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics, Nature Methods 12:258-64 (2015).
Demichev V, Yu F, Teo GC, Szyrwiel L, Rosenberger G, Decker J, Kaspar-Schoenefeld S, Lilley KS, Mülleder M, Nesvizhskii AI, Ralser M. High sensitivity dia-PASEF proteomics with DIA-NN and FragPipe, bioRxiv (2021).