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Using Tomoauto: A Protocol for High-throughput Automated Cryo-electron Tomography

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OpenTIMS, TimsPy, and TimsR: Open and Easy Access to timsTOF Raw Data.

Mateusz K Łącki¹, Michał P Startek², Sven Brehmer³

¹Institute of Immunology, University Medical Center of the Johannes-Gutenberg University Mainz, 55131 Mainz, Germany.

Journal of Proteome Research

|March 16, 2021

Summary

New software, OpenTIMS, TimsPy, and TimsR, provides accessible data retrieval for Bruker timsTOF Pro mass spectrometry. This enables broader analysis of proteomics, lipidomics, and metabolomics data.

Keywords:

OpenTIMS TimsPy data access ion mobility lipidomics mass spectrometry metabolomics proteomics raw data timsTOF

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Area of Science:

Mass Spectrometry
Analytical Chemistry
Biochemistry

Background:

Bruker timsTOF Pro couples trapped ion mobility spectrometry (TIMS) with time-of-flight mass spectrometry (MS).
LC-TIMS-MS data sets are large and stored in a proprietary Bruker TDF format.
Accessing raw timsTOF data typically requires proprietary binaries.

Purpose of the Study:

To introduce a suite of computer programs for accessing Bruker timsTOF Pro raw data.
To enable user-friendly and efficient data retrieval for proteomics, lipidomics, and metabolomics.
To extend the accessibility of timsTOF data to a wider range of users and platforms.

Main Methods:

Development of OpenTIMS, a C++ library for reading Bruker TDF files.
Creation of TimsPy and TimsR, Python and R packages built on OpenTIMS for data access.
Implementation of data translation to HDF5 format for analysis with Python's vaex module.

Main Results:

OpenTIMS facilitates direct access to Bruker's proprietary TDF files.
TimsPy and TimsR offer swift and user-friendly data access in Python and R.
The software suite supports all major platforms, including macOS, under a GPL3 license.

Conclusions:

OpenTIMS, TimsPy, and TimsR significantly improve access to Bruker timsTOF Pro raw data.
These tools democratize the analysis of complex omics data generated by timsTOF instruments.
The open-source nature and cross-platform compatibility enhance research reproducibility and collaboration.