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AutoLEI

Automated EffortLess MicroED Graphic User Interface (AutoLEI) is an XDS-based GUI designed for real-time and batch processing of MicroED/3DED datasets. It provides a user-friendly platform for rapid, automated data processing and merging of multiple MicroED datasets, with well-designed and significantly streamlining structure determination workflows.

Key Features

  • User-Friendly Interface: Simplifies MicroED data processing, requiring minimal manual input.
  • Batch Processing: Handles large numbers of datasets with automated workflows.
  • Real-Time Data Processing: Provides live feedback during data collection.
  • Versatility: Supports diverse samples, including small molecules and proteins workflow.

Installation

Requirements

  • Operating Systems: Linux or Windows via WSL (versions 1/2).
  • Software Dependencies:
    • Python 3.8+ with libraries specified in pyproject.toml.
    • XDS and XDSGUI.
    • Optional tools: xprep for advanced features and LibreOffice for .xlsx files in Linux.

Steps

  1. Install via pip:
    pip install autolei
    
    For historical versions, use:
    pip install autolei-[version_name].zip
    
  2. Manual installation: Follow the steps in the Tutorial for AutoLEI and our Wiki.

Usage

Command-line Usage

  • Launch the GUI:

    autolei
    

    Note: The first launch may take slightly longer as dependencies initialize.

  • Configure Settings:

    autolei_setting
    

    The opened .ini file includes settings on screen scaling, multi-thread and report format.

  • Import Instrument:

    autolei_add_instrument [instrument_setting_file]
    

GUI pages

AutoLEI is organised into multiple working pages:

  • Input: Configure experiment parameters and generate input files.
  • XDSRunner: Automate initial processing and data quality inspection.
  • CellCorr: Update unit cell information and refine settings.
  • XDSRefine: Fine-tune processing parameters, including rotation axis and scaling.
  • DataMerge: Filter and merge datasets for downstream analysis.
  • Cluster&Output: Perform clustering and generate outputs for structure determination.
  • Expert: Miscellaneous tools for data reduction and PETS related function.
  • RealTime: Live data processing with real-time feedback and automatic merging.

Documentation

Detailed guides and examples can be found in:


Authors and Acknowledgments

Developed by Lei Wang and Yinlin Chen. Contributions from Gerhard Hofer, Hongyi Xu, and Xiaodong Zou at Stockholm University. The project integrates valuable resources from edtools. Special thanks to the XDS team for their support and resources.


License

The software is licensed under the BSD 3-Clause License.

Metadata

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