Installation¶
This page details the install instructions for WIPAR.
Requirements¶
WIPAR supports Windows and Linux distributions. First, you need to install a Conda-based Python3 distribution like Anaconda. Then follow the install instructions for Snakemake.
Installation¶
Currently WIPAR is only available on Github, so you need to clone the repository to a folder of your choice. This folder will from now on be referenced as /WIPAR.
$ git clone https://github.com/michaelschaub/calcium-imaging-analysis.git
You should have the following file structure in your /WIPAR folder.
.
├── config (▶) | config files for pipeline runs
├── resources (▶) | experimental data and brain atlases
├── ci_lib (🛠) | python package containing all custom functions for the pipeline steps
├── workflow (🛠) | Snakemake logic like rules, envs and entry scripts
└── SLURM | batch files to run on computational clusters
(▶) Running & configuring pipeline (for User)
(🛠) Extending pipeline functions (for Developers)
Experimental Data¶
To run WIPAR you first need to provide the experimental data you want to process into the /WIPAR/resources/experiment/ folder in the following way
├── ...
├── resources
│ ├── meta
│ └── experiment
│ ├── subject1
│ │ ├── experiment_id1
│ │ ├── experiment_id2
│ │ └── ...
│ ├── subject2
│ │ ├── experiment_id1
│ │ ├── experiment_id2
│ │ └── ...
│ └── ...
├── ...
Each datasets is in a separate folder for each subject and each experiment_id (usual the time and date).
A concrete example for the path of a single dataset is /WIPAR/resources/experiment/GN06/2021-01-20_10-15-16.
Now you can test your installation with the example from the tutorial.
Note
If you encounter problems during the setup, please have a look at the trouble shooting