TIMSCONVERT

About

TIMSCONVERT is a workflow that allows for the conversion of raw data from Bruker timsTOF Pro, fleX, and SCP mass spectrometers (i.e. .d directory containing TDF and TSF files) to open source data formats (i.e. mzML and imzML). Examples for file conversion include:

• LC-TIMS-MS(/MS) (TDF) → mzML
  • Experiment Type: lc-tims-ms
• MALDI-MS(/MS) Dried Droplet (TSF) → mzML
  • Experiment Type: maldi-dd
• MALDI-MS Imaging Mass Spectrometry (TSF) → imzML
  • Experiment Type: maldi-ims
• MALDI-TIMS-MS(/MS) Dried Droplet (TDF) → mzML
  • Experiment Type: maldi-tims-dd
• MALDI-TIMS-MS Imaging Mass Spectrometry (TDF) → imzML (does not incorporate ion mobility data)
  • Experiment Type: maldi-tims-ims

Installation and Usage

GNPS Online Workflow

The web version of TIMSCONVERT currently only supports LC-TIMS-MS(/MS) data and can be found here. No installation is necessary. All that's required is a GNPS account.

1. Upload your data to GNPS (instructions).
2. Go to the TIMSCONVERT workflow page.
3. Select your dataset and parameters.
4. Submit your run.

Setting Up Your Local Environment

If you prefer to run TIMSCONVERT locally via Nextflow or the CLI, you can set up an environment to do so. Please note that TIMSCONVERT should be run under Linux or Windows Subsystem for Linux (WSL) if using Windows 10.

1. Download and install Anaconda. Follow the prompts to complete installation. Anaconda3-2021.11 is used as an example here.

wget https://repo.anaconda.com/archive/Anaconda3-2021.11-Linux-x86_64.sh
bash /path/to/Anaconda3-2021.11-Linux-x86_64.sh

2. Add anaconda3/bin to PATH.

export PATH=$PATH:/path/to/anaconda3/bin

3. Create a conda instance.

conda create -n timsconvert python=3.8

4. Activate conda environment.

conda activate timsconvert

5. (Optional, for Nextflow workflow only) Install Nextflow.

conda install -c bioconda nextflow

6. Download TIMSCONVERT by cloning the Github repo.

git clone https://www.github.com/gtluu/timsconvert

7. Install dependencies.

pip install -r /path/to/timsconvert/requirements.txt

Nextflow Workflow

Similar to the web version, the Nextflow workflow for TIMSCONVERT only supports LC-TIMS-MS(/MS) data currently.

1. Run the nextflow.nf script provided in this repo and specify your input directory and experiment type. Unless specified, all other default parameters for all other values will be used. See below for an explanation of all parameters.

nextflow run /path/to/timsconvert/nextflow.nf --input /path/to/your/data --experiment lc-tims-ms

2. Depending on the size of your data/number of files, TIMSCONVERT may take some time to finish conversion.

Command Line Interface

The CLI version of TIMSCONVERT supports conversion of all experimental data types specified above.

1. Use bin/run.py to run TIMSCONVERT. The input directory and experiment type. Unless specified, all other default parameters for all other values will be used. See below for an explanation of all parameters.

python3 /path/to/timsconvert/bin/run.py --input /path/to/data --experiment lc-tims-ms

2. Depending on the size of your data/number of files, TIMSCONVERT may take some time to finish conversion.

Parameters

Required
--input : Bruker .d file containing TSF/TDF or directory containing multiple Bruker .d files.

Optional
--experiment : Experiment performed to generate data. Should be lc-tims-ms, maldi-dd,
               maldi-tims-dd, maldi-ims, or maldi-tims-ims. Defaults to lc-tims-ms
--outdir : Path to folder in which to write output file(s). Defaults to .d source folder.
--outfile : User defined filename for output if converting a single file. If input is a folder
            with multiple .d files, this parameter should not be used as it results in each file
            overwriting the previous due to having the same filename.
--ms2_only : Boolean flag that specifies only MS2 spectra should be converted.
--ms1_groupby : Define whether an individual spectrum contains one frame (and multiple scans;
                "frame") or one scan only ("scan"). Defaults to "scan".
--encoding : Choose encoding for binary arrays. 32-bit ("32") or 64-bit ("64"). Defaults to 64-bit.
--maldi_output_file : For MALDI dried droplet data, whether individual scans should be placed in
                      individual files ("individual") or all into a single file ("combined").
                      Defaults to combined.
--maldi_plate_map : Plate map to be used for parsing spots if --maldi_output_file == "individual".
                    Should be a .csv file with no header/index.
--imzml_mode : Whether imzML files should be written in "processed" or "continuous" mode. Defaults
               to "processed".

System
--verbose : Boolean flag to determine whether to print logging output.

Testing

Get test data

cd test/data
sh ./get_data.sh

Run workflow

make run_test

Changelog

v 1.0.0

• Initial release.