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Merge pull request #193 from ansgarkorf/performance-and-citations-update
Performance and citations update
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docs/citations.md

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# Citations
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How to cite different parts of MZmine: Workflows, tools, etc.
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How to cite different parts of mzmine: Workflows, tools, etc.
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docs/contribute_docu_template.md

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## Recommended citations
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!!! info
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When using MZmine 3 for your work, please consider citing:<br>
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When using mzmine for your work, please consider citing:<br>
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Schmid R., Heuckeroth S., Korf A., et al. Integrative analysis of multimodal mass spectrometry data in MZmine 3, Nature Biotechnology (2023), doi:10.1038/s41587-023-01690-2.
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When using this modules, please consider citing the corresponding publication(s):<br>

docs/performance.md

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# General remarks
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This section contains information on how to tune MZmine 3 for different systems. Generally these points can improve the throughput and memory constraints:
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This section contains information on how to tune mzmine for different systems. Generally these points can improve the throughput and memory constraints:
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- Check the latest [**Processing Wizard**](wizard.md) workflows that may contain new modules and options to speed up and enrich your analysis. You may want to remove unnecessary steps.
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- Make sure to set the **temporary** files directory to a **fast local drive**, e.g., SSD
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- [Convert files](data_conversion.md) to centroided open formats, e.g., mzML
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- Run MZmine in **headless mode** as a [command-line tool](commandline_tool.md) to avoid the graphical-user interface (GUI). Just provide a batch file and process on any computer or server.
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- Run mzmine in **headless mode** as a [command-line tool](commandline_tool.md) to avoid the graphical-user interface (GUI). Just provide an .mzbatch file and process on any computer or server.
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- Use the **advance data import** to reduce the amount of data that needs to be loaded. This will apply mass detection during the import.
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- Optimize your MZmine workflow in the batch mode, cosidering your data and study design:
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- Optimize your mzmine workflow in the batch mode, considering your data and study design:
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- Increase minimum feature height, noise levels, and other feature constraints. If a feature was detected in at least one sample - gap-filling will try to fill the gaps of missed features later.
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- Use **Join aligner** and **Peak finder (multi-threaded)** gap-filling for large datasets as they are optimized
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- Use **Join aligner** and **Peak finder (multithreaded)** gap-filling for large datasets. Both modules are optimized for performance.
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- Apply **Rows filter** between alignment and gap-filling with a minimum number of samples filter: "How many samples do I need for a significant feature?"
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- Set all **Handling orgininal feature lists** parameters to *PROCESS IN PLACE* or *REMOVE*
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- Set all **Handling original feature lists** parameters to *PROCESS IN PLACE* or *REMOVE*
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- Upgrade the **RAM** of your system or run on a server
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## Tuning modules
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### Advanced data import
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The advanced data import provides the option to apply mass detection during import and only
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loading those filtered mass spectra. This is a great way to reduce the need for memory
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mapping of raw spectra that are not used in most workflows (most use the masslists detected
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by Mass detection step as a filtered centroid version of spectra). This option is great for large datasets and for profile mode data.
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by Mass detection step as a filtered centroid version of spectra).
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This option is great for large datasets and for profile mode data.
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1. Open the Import MS data parameters
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2. Activate Advanced import and press Setup
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3. Define the MS1 and MS2 detectors as described in the Mass detection step
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4. Remove all other Mass detection steps from the batch configuration, usually applied after data import
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![Advanced import](img/advanced_import.png)
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### Handling orgininal feature lists
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Most processing steps in MZmine create new feature lists and have options to handle the orgininal lists.
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### Handling original feature lists
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Most processing steps in mzmine create new feature lists and have options to handle the original lists.
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- KEEP: Use during optimization of the workflow. All feature lists are kept for comparison purposes and to backtrack issues.
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- REMOVE: Remove the original feature lists. Better for performance and memory constraints on large datasets.
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- PROCESS IN PLACE: Only available for some modules like the duplicate filter or the rows filter. Even better performance then REMOVE.
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## Preferences
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The preferences can be changed in MZmine's graphical user interface by accessing _File/Set
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The preferences can be changed in mzmine's graphical user interface by accessing _File/Set
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preferences_ from the menu. The choices will be stored in a (hidden) _.mzmine3.conf_ file in the
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user's home directory (Windows: _C:\Users\USERNAME_) once MZmine is closed.
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user's home directory (Windows: _C:\Users\USERNAME_) once mzmine is closed.
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![Preferences](img/menu_pref.png){: style="width:200px"}
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### Temporary files
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MZmine will create multiple temporary files at various times of the processing stage, e.g., when
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mzmine will create multiple temporary files at various times of the processing stage, e.g., when
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importing spectral data, running mass detection, or creating feature lists. These files will be
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stored in a folder that can be specified in the preferences.
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We recommend putting this folder on an SSD drive, ideally an M.2 for the best performance. The
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temporary files will be deleted when MZmine is closed (Mac & Linux) or when a new session is
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started (Windows).
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We recommend putting this folder on an SSD drive, ideally an M.2 for the best performance. Until version < 4.3 the
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temporary files were deleted when mzmine was closed (Mac & Linux) or when a new session is
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started (Windows). With mzmine version 4.3 > temporary files are deleted as soon as possible.
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![tempdir](img/performance_param.png){: style="width:500px"}
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## Logs
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Currently, the logs are written to an _mzmine_0_0.log_ file in the user's home directory. Please
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Currently, the logs are written to the _mzmine_0_0.log_ file in the user's home directory. Please
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submit your log files together with any issues
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on **[GitHub](https://github.com/mzmine/mzmine3/issues)**.
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## Maximum memory
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The maximum Java heap size (the main part of the RAM available to MZmine) is set to 80%. This is usually a good value, considering that MZmine and its Java Virtual Machine (JVM) will use memory extending over this 80% threshold for specific tasks. There is one way to change the maximum heap size before starting MZmine, however, it requires administrator access.
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The maximum Java heap size (the main part of the RAM available to mzmine) is set to 80%. This is usually a good value, considering that mzmine and its Java Virtual Machine (JVM) will use memory extending over this 80% threshold for specific tasks. There is one way to change the maximum heap size before starting mzmine, however, it requires administrator access.
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Find the **MZmine/app/MZmine.cfg** file in the MZmine install directory or portable version. Under Window, this file is write protected, which needs to be changed under **File/Properties/Security/** select Users and click Edit to grant write access. Now change the _MaxRAMPercentage_ to grant more RAM.
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Find the **mzmine/app/MZmine.cfg** file in the mzmine install directory or portable version. Under Window, this file is write protected, which needs to be changed under **File/Properties/Security/** select Users and click Edit to grant write access. Now change the _MaxRAMPercentage_ to grant more RAM.
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```
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java-options=-XX:InitialRAMPercentage=10
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java-options=-XX:MaxRAMPercentage=80

mkdocs.yml

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- Performance options: performance.md
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- Command line tool (batch mode): commandline_tool.md
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- Integration to other tools: tool_integration.md
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- Citations: citations.md
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# - Citations: citations.md
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- Processing modules:
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- I/O:

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