Use of STRonGR¶

TLDR¶

Click on your field of interest (expression, variant calling, …). Click on your pipeline. Copy / paste command lines.

More information:¶

The whole documentation can be used by itself, however STRonGR can mange the installation, preparation, execution, and tests by following the instructions you may read in the dedicated docs.

This documentation is powered by a workflow manager called STRonGR. STRonGR can help you produce scripts that executes the pipelines documented here after (see the left side bar!). In order to make so, it produces a bash script which you can freely read, modify and/or run.

This bash script contains automatically created environment variables (which you can see here and there in the command lines provided in the rest of the documentation), and uses a command line scheme extracted from the documentation itself.

This means STRonGR does not intend to run your pipelines, rather than give you the best practices described in each pipeline’s documentation. Running STRonGR produces a bash file. This bash file should be modified, but in case you feel lucky, then use the corresponding argument.

Environment variables within STRonGR¶

When one uses STRonGR, one gets a bash file that is to be executed.

However, along the help pages, you might have seen environment variables like RNA_COUNT_KALLISTO_DIR. Do not worry, this is one of the environment variables set by STRonGR within the bash script produced.

The environment variables are build as follows: prefix + “_” + suffix. The are always both UPPER CASE, and snake_case. No exception.

There are two possible prefix:

STRONGR, which is used to point to STRonGR itself

PIPELINE_NAME, which is used to refer to the pipeline you use. Example: rna-count-kallisto has the following prefix: RNA_COUNT_KALLISTO. Everything is upper case, dash have been turned into underscores.

There are the possible suffixes:

DIR, which refers to the directory that contains the given prefix. Example: STRONGR_DIR is the installation path of STRonGR. RNA_COUNT_KALLISTO_DIR is the installation path of rna-count-kallisto.

PREPARE_DIR, which refers to the directory containing raw data. Example: RNA_COUNT_KALLISTO_PREPARE_DIR contains the raw data (fastq reads) for the pipeline rna-count-kallisto

Running STRonGR¶

In order to use STRonGR workflow manager, call the help:

# Here, we consider that your installation of STRonGR is complete
conda activate STRonGR

python3.7 STRonGR_cli.py --help

You will see the list of existing pipelines. You can now call a specific pipeline. For this example, we will use cel-cnv-eacon:

python3.7 STRonGR_cli.py cel-cnv-eacon --help

If you open the documentation and your teminal side by side, you’ll understand easily that STRonGR reads the docs and offers you to execute the command lines displayed in there.

Each key-word present in preparation, execution, installation and testing are available within STRonGR command line. Here, for cel-cnv-eacon, the documentation gives three installation steps: one with conda, one with additional libraries, and one using the git copy.

In the command line, cel-cnv-eacon pipeline within STRonGR will take a key-word argument –install which will take one or more arguments among : conda, additional, and git.

The section “notes” of the help explains that: conda stands for requirements for EaCoN, additional for supplementary annotations and EaCoN itself, and git for the repository cloning from github.

From a computer without EaCoN installed, we would run the following command line in order to install cel-cnv-eacon:

python3.7 STRonGR_cli.py cel-cnv-eacon --install conda additional git

However, if EaCoN were already installed, then we would only have to clone the git repository:

python3.7 STRonGR_cli.py cel-cnv-eacon --install git

Each of these command lines produces a bash script. If we feel lucky and want to execute these bash scripts right away without checking them before, then we would have used the argument –lucky:

# For a complete installation:
python3.7 STRonGR_cli.py cel-cnv-eacon --install conda additional git --lucky

# For a git clone only:
python3.7 STRonGR_cli.py cel-cnv-eacon --install git --lucky

The very same goes with the rest of the arguments: –prepare can take one or more of the following values: activate, design, local, and igr_cigogne.

According to the documentation, we can see that each of these key-words are associated with a command line. If we want to prepare a local run for cel-cnv-eacon, then we need use:

python3.7 STRonGR_cli.py cel-cnv-eacon --prepare activate design local

This will produce a bash script with corresponding command lines, ready to be executed. If we had felt lucky today, We could have run it right away without any verification thanks to the argument –lucky:

python3.7 STRonGR_cli.py cel-cnv-eacon --prepare activate design local --lucky

Finally, for the argument –execute, cel-cnv-eacon pipeline within STRonGR will take one or more arguments among : local, torque, slurm, and report.

If we feel lucky and want to execute our cen-cnv-eacon pipeline locally, we would do:

python3.7 STRonGR_cli.py cel-cnv-eacon --execute local --lucky

Note that an optional report can be built with Snakemake! If we want to add an extra report in our pipeline, then we would write:

python3.7 STRonGR_cli.py cel-cnv-eacon --execute local report --lucky

Remember, the order of the values after a key-word argument is preserved within the final bash script!