uMAIA 0.2

Toolbox for the processing and analysis of MALDI-MSI data

uMAIA

Toolbox for the processing and analysis of MALDI-MSI data

Installation

To begin, create a new environment with conda create --name uMAIA_env python==3.9

activate the environment with conda activate uMAIA_env

conda install jupyter with conda install jupyter

install the required packages pip install -r requirements.txt

If you are experiencing issues during the installation with caches files, you may need to remove them. You can do so with the following commands: conda clean -a python -m pip cache purge rm ~/.cache/pip -rf conda update --all

Gurobi

The molecule matching portion of the pipeline requires Gurobi. You will need to (1) install the Gurobi installer and (2) activate a license that is free for those are affiliated with an academic institution. Concerning (1), download the archive with

Linux: wget https://packages.gurobi.com/9.1/gurobi9.1.2_linux64.tar.gz to the directory you want to install it in. or MacOS: https://packages.gurobi.com/9.1/gurobi9.1.2_macos_universal2.pkg

Unpack the archive with

Linux: tar -xzvf gurobi9.1.2_linux64.tar.gz or on MacOS, simply double click the .pkg file and walk through the installation instructions

Activate the license with

Linux: gurobi912/linux64/bin/grbgetkey <licensekey> MacOS: grbgetkey <licensekey>

GPU usage restrictions

If you intend on applying uMAIA's normalisation algorithm on a GPU, please note that JAX will automatically use between 75 and 90 % of available GPU memory. To indicate that you would only like to allocate memory that is needed, you may export an environment variable after activating the environment with export XLA_PYTHON_CLIENT_PREALLOCATE=false