Docker is a flexible and popular container management platform. With only few steps, you can obtain a full OpenSWATH installation including all dependencies on Windows, macOS and Linux. The OpenSWATH docker container will continuously be updated to the latest development version.
Users who just want to run the OpenSWATH workflow on their desktops can follow the instructions below to obtain an installation-free, always-updated workflow. It will run with nearly native speed on desktops, clusters and cloud environments.
First, install Docker Community Edition for either Windows, macOS or Linux. On Linux, most current distributions provide this out-of-the-box. After installation, ensure that you assign the number of CPUs and RAM that you would like to use with OpenSWATH (e.g. 4 CPUs, 8GB RAM) and make sure to share your local drives. Please follow the instructions for Windows and macOS.
Running OpenSWATH in Docker¶
Make sure that Docker is up and running in the background. On macOS or Linux, start a Terminal session. On Windows, start PowerShell, CMD or similar. Execute the following steps within the console:
# Download OpenSWATH image (grosenberger/openswath:latest) docker pull grosenberger/openswath:latest
This will download the latest version of the OpenSWATH Docker image and cache it on your machine.
Official containers for OpenMS and related tools are available via BioContainers. The image provided here provides the latest development version including related tools.
# Generate tutorial container (osw_tutorial) and log in docker run --name osw_tutorial --rm -v ~/Desktop/:/data -i -t grosenberger/openswath:latest
This command will start a container based on the OpenSWATH image and map the local volume
~/Desktop/ (from your desktop) to
/data/ (to your container). It will open a Bash command line within the container for you to control the individual components of the workflow. If you want to exit the session, just type
exit to return to your console.
Within the running container, you can execute all commands as you would in a native environment:
# Execute OpenSwathWorkflow in docker OpenSwathWorkflow --help # Execute PyProphet in docker pyprophet --help # Execute TRIC in docker feature_alignment.py --help
All data that will be stored in
~/Desktop, will be available in
/data/. For example, we can process and write back the files like this:
OpenSwathWorkflow \ -in /data/data.mzML -tr /data/library.tsv \ -tr_irt /data/iRT_assays.TraML \ -swath_windows_file /data/SWATHwindows_analysis.tsv \ -sort_swath_maps -batchSize 1000 \ -readOptions cacheWorkingInMemory -tempDirectory /tmp/ \ -use_ms1_traces \ -mz_extraction_window 50 -ppm \ -mz_correction_function quadratic_regression_delta_ppm \ -TransitionGroupPicker:background_subtraction original \ -RTNormalization:alignmentMethod linear \ -Scoring:stop_report_after_feature 5 \ -out_tsv /data/osw_output.tsv \