Advanced Usage

Docker Container Installation and Usage

A Dockerfile has also been provided to run TIMSCONVERT inside a Docker container.

1. Build the Docker image.

   docker build --tag timsconvert -f [path to]/timsconvert/Dockerfile .
   

2. Run the Docker image in a container.

   docker run --rm -it -v [path to data]:/data timsconvert --input /data --outdir /data
   

Nextflow Installation and Usage

A Nextflow workflow has also been provided to run TIMSCONVERT.

1. Create a conda instance. You must be using Python 3.11. Newer versions of Python are not guaranteed to be compatible with Bruker’s API in Linux.

   conda create -n timsconvert python=3.11
   

2. Activate conda environment.

   conda activate timsconvert
   

3. Install Nextflow to your conda environment.

   conda install -c bioconda nextflow
   

3. Download TIMSCONVERT by cloning the Github repo.

   • You will need to have Git installed and ensure that the option to enable symbolic links was checked during installation.

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

   • It may be necessary to explicitly allow for the use of symbolic links by adding the -c core.symlinks=True

   git clone -c core.symlinks=true https://www.github.com/gtluu/timsconvert
   

4. Install TIMSCONVERT’s dependencies via pip.

   pip install -r [path to timsconvert directory]/requirements.txt
   

5. You will also need to install our forked version of pyimzML, which has added support for ion mobility arrays in imzML data from imaging mass spectrometry experiments.

   pip install git+https://github.com/gtluu/pyimzML
   

6. Configure nextflow.nf script to your liking. See Local Usage for a list of parameters.

7. Run TIMSCONVERT in Nextflow.

   nextflow run [path to timsconvert]/nextflow.nf --input [path to your data]