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FragPipe is a comprehensive computational platform for analyzing mass spectrometry-based proteomics data. FragPipe comes with an easy to use Java Graphical User Interface (GUI) but can also be run in the command line mode, on Windows, Linux, or in the cloud environment. It is powered by [MSFragger](https://msfragger.nesvilab.org/) - an ultrafast proteomic search engine suitable for both conventional and "open" (wide precursor mass tolerance) peptide identification. FragPipe includes Percolator and the [Philosopher](https://nesvilab.github.io/philosopher/) toolkit for downstream post-processing of MSFragger search results (PeptideProphet, iProphet, ProteinProphet), FDR filtering, label-based quantification, and multi-experiment summary report generation. FragPipe includes MSBooster module for deep-learning based rescoring of peptide identifications. [Crystal-C](https://www.nesvilab.org/Crystal-C/) and [PTM-Shepherd](https://github.com/Nesvilab/PTM-Shepherd) are included to aid interpretation of open search results. Also included in FragPipe binary are [TMT-Integrator](http://tmt-integrator.nesvilab.org/) for TMT/iTRAQ isobaric labeling-based quantification, [IonQuant](http://ionquant.nesvilab.org/) for label-free quantification with FDR-controlled match-between-run (MBR) functionality, spectral library building with EasyPQP, and MSFragger-DIA, DIA-Umpire SE, and diaTracer modules for direct ("library-free") analysis of data independent acquisition (DIA) data. FragPipe includes DIA-NN for extraction of quantification from DIA data.
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FragPipe is a comprehensive computational platform designed for the analysis of mass spectrometry-based proteomics data. It includes a Graphical User Interface and pipeline wrapper code (FragPipe-GUI), distributed alongside various independent software tools and workflow files. FragPipe can be run using GUI or in the command line mode, on Windows, Linux, or in the cloud environment. It is powered by [MSFragger](https://msfragger.nesvilab.org/) - an ultrafast proteomic search engine suitable for both conventional and "open" (wide precursor mass tolerance) peptide identification. FragPipe includes Percolator and the [Philosopher](https://nesvilab.github.io/philosopher/) toolkit for downstream post-processing of MSFragger search results (PeptideProphet, iProphet, ProteinProphet), FDR filtering, and multi-experiment summary report generation. FragPipe includes MSBooster module for deep-learning based rescoring of peptide identifications. [Crystal-C](https://www.nesvilab.org/Crystal-C/) and [PTM-Shepherd](https://github.com/Nesvilab/PTM-Shepherd) are included to aid interpretation of results from "open" and "mass offset" searches for post-translational modifications (PTM). FragPipe supports all modes of quantification, including MS1-based isotope labeling (e.g. SILAC) or MS1-based label-free quantification with FDR-controlled match-between-run (LFQ-MBR) using IonQuant [IonQuant](http://ionquant.nesvilab.org/), TMT/iTRAQ isobaric labeling-based quantification using IonQuant and [TMT-Integrator](http://tmt-integrator.nesvilab.org/). FragPipe provides a comprehensive list of workflows for the analysis of data independent acquisition (DIA) data with MSFragger-DIA, DIA-Umpire/MSFragger, and diaTracer/MSFragger workflows for direct ("library-free") peptide identification from DIA files, spectral library building with EasyPQP, and extraction of quantification using DIA-NN and Skyline.
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_DIA data acquired with overlapping/staggered windows must be [converted to mzML with demultiplexing](https://fragpipe.nesvilab.org/docs/tutorial_convert.html#convert-thermo-dia-raw-files-with-overlappingstaggered-windows)._
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_Quantification from Thermo .raw files with DIA-NN requires installation of Thermo MS File Reader, see the [DIA-NN documentation](https://github.com/vdemichev/DiaNN#raw-data-formats) for details._
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Please note TMT/iTRAQ quantification from Thermo .raw files will take longer than from .mzML files.
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#### Additional Documentation
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Complete MSFragger documentation can be found on the [MSFragger wiki](https://github.com/Nesvilab/MSFragger/wiki).
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For documentation on the Philosopher toolkit see the [Philosopher wiki](https://github.com/Nesvilab/philosopher/wiki).
[FragPipe issue tracker](https://github.com/Nesvilab/FragPipe/issues). Please post any new questions/bug reports regarding FragPipe itself here as well.
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For questions specific to individual components of FragPipe you can also
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use [MSFragger issue tracker](https://github.com/Nesvilab/MSFragger/issues),
For other tools developed by Nesvizhskii lab, visit our website
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[nesvilab.org](http://www.nesvilab.org)
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#### How to Run
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-**Windows**:
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-Double click the `FragPipe.exe` or `FragPipe.bat` from the `bin` folder
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-Or execute the command: `java -jar FragPipe-x.x.jar`
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-Install FragPipe by double-clicking the `FragPipe-x.x-Installer.exe`
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-Double click the `FragPipe-x.x.exe` at the Desktop
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-**Linux**:
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- Run the `fragpipe` shell script (can double-click to run)
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- Or execute the command: `java -jar FragPipe-x.x.jar`
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-**Mac OS** (command line interface only):
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- Read [Pulling and running FragPipe using Docker](https://fragpipe.nesvilab.org/docs/tutorial_docker.html)
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#### Integration
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FragPipe is open source and the output is currently supported by the following software projects:
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#### Key references
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##### Database search
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- Kong, A. T., Leprevost, F. V., Avtonomov, D. M., Mellacheruvu, D., & Nesvizhskii, A. I. (2017). MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry–based proteomics. Nature Methods, 14(5), 513-520.
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- Yu, F., Teo, G. C., Kong, A. T., Haynes, S. E., Avtonomov, D. M., Geiszler, D. J., & Nesvizhskii, A. I. (2020). Identification of modified peptides using localization-aware open search. Nature Communications, 11(1), 1-9.
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- Yu, F., Teo, G. C., Kong, A. T., Haynes, S. E., Avtonomov, D. M., Geiszler, D. J., & Nesvizhskii, A. I. (2020). Identification of modified peptides using localization-aware open search. Nature Communications, 11, 4065.
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- Yu, F., Haynes, S. E., Teo, G. C., Avtonomov, D. M., Polasky, D. A., & Nesvizhskii, A. I. (2020). Fast quantitative analysis of timsTOF PASEF data with MSFragger and IonQuant. Molecular & Cellular Proteomics, 10(9), 1575-1585.
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- Teo, G. C., Polasky, D. A., Yu, F., Nesvizhskii, A. I. (2020). A fast deisotoping algorithm and its implementation in the MSFragger search engine. Journal of Proteome Research, 20(1), 498-505.
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##### Chimeric spectra search
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- Yu, F., Deng, Y. & Nesvizhskii, A.I. (2025). MSFragger-DDA+ enhances peptide identification sensitivity with full isolation window search. Nature Communications, 16, 3329.
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##### Glyco/Labile search
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- Polasky, D. A., Yu, F., Teo, G. C., & Nesvizhskii, A. I. (2020). Fast and Comprehensive N-and O-glycoproteomics analysis with MSFragger-Glyco. Nature Methods, 17, 1125-1132.
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- Polasky, D. A., Geiszler, D. J., Yu, F., & Nesvizhskii, A. I. (2022). Multiattribute Glycan Identification and FDR Control for Glycoproteomics. Molecular & Cellular Proteomics, 21(3), 100205.
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- Polasky, D. A., Geiszler, D. J., Yu, F., Kai, Li., Teo, G. C., & Nesvizhskii, A. I. (2023). MSFragger-Labile: A Flexible Method to Improve Labile PTM Analysis in Proteomics. Molecular & Cellular Proteomics, 22(5), 100538.
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- Polasky, D. A., Lu, L., Yu, F., Li, K., Shortreed, M. R., Smith, L. M., & Nesvizhskii, A. I. (2025). Quantitative proteome-wide O-glycoproteomics analysis with FragPipe. Analytical and Bioanalytical Chemistry, 417(5), 921-930.
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##### PTM
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##### DIA
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- Tsou, C. C., Avtonomov, D., Larsen, B., Tucholska, M., Choi, H., Gingras, A. C., & Nesvizhskii, A. I. (2015). DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics. Nature methods, 12(3), 258-264.
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- Yu, F, Teo, G. C., Kong, A. T., Fröhlich, K., Li, G. X. , Demichev, V, Nesvizhskii, A..I. (2023). Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform, Nature Communications 14:4154.
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- Yu, F, Teo, G. C., Kong, A. T., Fröhlich, K., Li, G. X. , Demichev, V, Nesvizhskii, A..I. (2023). Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform, Nature Communications 14, 4154.
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##### DIA-PASEF
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- Li, K., Teo, G. C., Yang, K. L., Yu, F., & Nesvizhskii, A. I. (2025). diaTracer enables spectrum-centric analysis of diaPASEF proteomics data. Nature Communications, 16, 95.
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##### DDA quantification
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#### Building from scratch
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1. Update build version:
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The version of the build is stored in 3 separate places:
You don't need to have Gradle installed, the Gradle wrapper included in this repository will be used. From the root directory of the repository issue the following commands:
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```bash
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cd ./MSFragger-GUI
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./gradlew makeReleaseZipNoJre
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```
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or use this version to build with Java Runtime (for Windows only):
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```bash
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cd ./MSFragger-GUI
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./gradlew makeReleaseZipWithJre
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```
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```bash
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cd FragPipe-GUI
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./gradlew makeReleaseInstaller # for Windows
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./gradlew makeReleaseZipLinux # for Linux
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```
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3. The .zip output will be in `MSFragger-GUI/build/github-release`.
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The `FragPipe-x.x-Installer.exe` will be in the `FragPipe-GUI/build/installer` directory.
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The `FragPipe-x.x-linux.zip` will be in the `FragPipe-GUI/build/github-release` directory.
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