Scripts for simulating high-resolution imaging mass spectrometry datasets.

Usage

Prerequisites

1. miniconda (see Install miniconda for Python 2.7)
2. git (see Getting Started Installing Git)

Installation

1. Create a directory for this repository

mkdir ~/projects/ims_simulator/

2. Clone this repository

   cd ~/projects/ims_simulator/
   git clone https://github.com/SpatialMetabolomics/ims-simulator.git
   

3. Set up a virtual environment for the code

cd ims-simulator/
conda env create
source activate ims_simulator

How to get a simulated .imzML from a real .imzML

1. Create a working directory where all generated files will be kept (mkdir -p ~/projects/ims_simulator/data/test/ && cd ~/projects/ims_simulator/data/test/).
2. Copy example_config.yaml from to the newly created directory cp ~/projects/ims_simulator/ims-simulator/example_config.yaml ~/projects/ims_simulator/data/test/config.yaml
3. Open the config.yaml file in your favourite text editor and change the imzml: field to be a centroided .imzml dataset you wish to use as a template for the simulation (the default is an example file provided along with this repository)
4. Run python ~/projects/ims_simulator/ims-simulator/pipeline.py ~/projects/ims_simulator/data/test/config.yaml from the directory and wait. In about an hour it should successfully finish.
5. If the run completes without errors, you will find a file named report_<config hash>.pdf along with the generated imzML file. It contains some useful metrics for comparing simulated and original datasets.

Funding

This project is funded from the European Horizon2020 project METASPACE (no. 634402), NIH NIDDK project KPMP and internal funds of the European Molecular Biology Laboratory.

License

Unless specified otherwise in file headers, all files are licensed under the Apache 2.0 license.