This pipeline leverages the snakemake Python package for workflow management. As a result the pipeline and its dependencies are easily installed from this repository, allowing quick setup, configuration and deployment.

For more information on Snakemake, please see: https://snakemake.readthedocs.io/en/stable/.

Dependency management for this pipeline is handled via conda for Python and renv for R. To get started with setup you can install miniconda3 using the instructions available here: https://docs.conda.io/en/latest/miniconda.html.

Alternatively you can install it directly from CRAN as described here: https://cran.r-project.org/.

The first step to deploying an analysis pipeline is to install the various software packages it depends on. We have included the envs/merida.yaml and renv.lock files here to easily accomplish this.

All commands should be executed from the top level directory of this repository.

This pipeline requires the use of IBM ILOG CPLEX logical solver, which is closed source software. An academic license can be obtained from IBM to use this software for free. Follow the instructions on Compute Canada.

We recommend also setting the CPLEX_HOME environmental variable to make it easy for compiled code to find your installation. You can set it with:

NOTE: replace /path/to/CPLEX_StudioXYZ with your CPLEX path and version before running! A back-up of your .bashrc will be saved in ~/.bashrc.bak if something goes wrong with this script.

# Delete existing the line containg CPLEX_HOME in-place, if it exists
sed -i.bak '/CPLEX_HOME=.*/d' ~/.bashrc
# Add new CPLEX_HOME
echo "export CPLEX_HOME=/path/to/CPLEX_StudioXYZ" >> ~/.bashrc
# Reload .bashrc
source ~/.bashrc
# Check that the variable exists
echo $CPLEX_HOME

This will set an environmental variable in your ~/.bashrc file, then reload your enviroment variables from .bashrc and print the path. If the command doesn't print your the path you configured it has failed and may need to be fixed manually.

If you are on Windows, the environmental variable should be created automatically by the CPLEX installer. Please note this pipeline has not been tested on Windows and may not work correctly.

Conda can be used to install all Python and most OS system dependencies using:

conda env create --file envs/merida.yml

This will take some time to run as it gathers and installs the correct package versions. The environent it creates should be called merida.

If it is not automatically activated after installation please run conda activate merida before proceeding to the next step.

The renv package can be used to install all R dependencies (both CRAN and Bioconductor). R version 4.1 and renv are included as dependencies in the merida.yml file and should be installed automatically when setting up your conda environment. If R is not installed, you can install it via conda using the command: conda -c conda-forge R==4.1.1.

To initialize this project with renv run:

Rscript -e 'library(renv); renv::init()'

If you wish to isolate the R dependencies from your Conda environment R libraries, you can use this command instead:

Rscript -e 'library(renv); renv::isolate(); renv::init(bare=TRUE)'

If intialization doesn't trigger dependency installation, you can do so manually using:

Rscript -e 'renv::restore()'

For more information on renv and how it can be used to manage dependencies in your project, please see: https://rstudio.github.io/renv/articles/renv.html.

If the renv commands fail, you may need to install renv manually with Rscript -e 'install.packages("renv")' then retry the above commands.

This pipeline assumes the following directory structure:

.
├── envs
├── src
├── bin
├── metadata
├── rawdata
├── procdata
├── results
└── scripts

Please at minimum create the rawdata and metadata directories. The remainder will be created automatically during pipeline execution.

This file hold the relevant pipeline documentation. Here you can specify the paths to all the parameters for your current pipeline use case. Documentation is provided in the config.yaml file on what each field should contain.

Make sure you have set all values in config.yml before trying to run the pipeline! This file contains all user configuration necessary to get the pipleine running with your specific data and project structure.

snakemake --cores 2 download_and_compile_merida

snakemake --cores

snakemake --cores

snakemake --cores