About

This workflow uses a modified version of TIMSCONVERT to take multiple raw MALDI-qTOF Dried Droplet MS datasets from the Bruker timsTOF fleX from successive AutoXecute runs with different, non-overlapping mass range windows and combines them into a single consensus spectrum with the “full” mass range.

Installation

Installing on Windows

  1. Download and install Anaconda for Windows if not already installed. Follow the prompts to complete installation.

  2. Download and install Git for Windows if not already installed.

  3. Run Anaconda Prompt.

  4. Create a conda instance.

    conda create -n maldi_polymerization python=3.11

  5. Activate conda environment.

    conda activate maldi_polymerization

  6. Install dependencies.

    pip install -r https://raw.githubusercontent.com/gtluu/flex_maldi_dda_automation/gui/maldi_polymerization/requirements.txt

  7. Simply clone the flex_maldi_dda_automation repo or download the standalone script here.

  8. See below for usage information and example.

Installing on Linux

  1. If not already installed, download and install Anaconda for Linux. Anaconda3-2023.07-2 for Linux is used as an example here.

    • Alternatively, the script can be downloaded in the Terminal using the following command.

    wget https://repo.anaconda.com/archive/Anaconda3-2023.07-2-Linux-x86_64.sh

  2. If not already installed, install git. On Ubuntu 23.04.3 LTS, this can be done using the following command.

    sudo apt-get install git

  3. Install Anaconda for Linux via the bash script that was downloaded. After installation, restart the terminal (or open a new terminal window).

    bash [path to]/Anaconda3-2023.07-2-Linux-x86_64.sh

  4. In the terminal, create a conda virtual environment.

    conda create -n maldi_polymerization python=3.11

  5. Activate conda environment.

    conda activate maldi_polymerization

  6. Install dependencies.

    pip install -r https://raw.githubusercontent.com/gtluu/flex_maldi_dda_automation/gui/maldi_polymerization/requirements.txt

  7. Simply clone the flex_maldi_dda_automation repo or download the standalone script here.

  8. See below for usage information and example.

Usage

This workflow is run from the command line.

Parameters

--input: One or more MALDI-MS .d directories acquired from the timsTOF fleX in successive AutoXecute runs with different, non-overlapping mass range windows.

--output: Name of the resulting mzML file.

--mode: Choose whether to export to spectra in profile, centroid, or raw mode. Defaults to centroid.

--compression: Choose between ZLIB compression (zlib) or no compression (none). Defaults to zlib.

--encoding: Choose encoding for binary arrays: 32-bit (32) or 64-bit (64). Defaults to 64-bit.

--barebones_metadata: Only use basic mzML metadata. Use if downstream data analysis tools throw errors with descriptive CV terms.

Example

python maldi_polymerization/maldi_polymerization.py --input strain1_mr1.d strain1_mr2.d strain1_mr3.d --output test.mzML