Installation

DROP is available on bioconda . In case the conda channel priority is set to strict, it should be reset to flexible:

conda config --set channel_priority true

We recommend using a dedicated conda environment (here: drop_env) for installing DROP. Use mamba instead of conda as it provides more reliable and faster dependency solving.

mamba create -n drop_env -c conda-forge -c bioconda drop --override-channels

In the case of installation troubles, we recommend using the fixed DROP_<version>.yaml installation file available on our public server. Install the latest version and use the full path in the following command to install the conda environment drop_env

mamba env create -f DROP_1.3.0.yaml

Installation time: ~ 10min

We can test whether the pipeline runs through by setting up the demo dataset in an empty directory (e.g. ~/drop_demo).

conda activate drop_env
mkdir ~/drop_demo
cd ~/drop_demo

# this command will download the necessary data and pipeline files
drop demo

DROP is run using snakemake commands.

Run time: ~25min

snakemake --cores 1 -n # dryrun
snakemake --cores 1

Initialize a project

The config and sample annotation files from the demo project can be modified to be used for a new project. Alternatively, a new DROP project can be set up using drop init.

cd <path/to/project>
drop init

This will create an empty config.yaml file that needs to be filled according to the project data. You also need to prepare a sample annotation file. Go to Preparing the Input Data for more details.

Other DROP versions

The following instructions are for users who have not used conda to install DROP previously. In order for the pip installation to take effect, you must first uninstall any previous installation using the following command. If you have not installed DROP previously, then there is no need to uninstall it.

pip uninstall drop

Other versions of DROP, such as dev can be found in the repository under different branches. Make sure that the Installation without conda are installed, preferably in a conda environment. Then install the desired version (e.g. dev in this example) from GitHub using pip.

pip install git+https://github.com/gagneurlab/drop.git@dev

Alternatively, you can clone the desired branch of the repository and install from directory.

git clone -b dev https://github.com/gagneurlab/drop.git
pip install ./drop

If the package needs to be updated frequently, it is more convenient to use the -e option of pip. Any new update pulled from the repository will be available without reinstall. Note, that this requires an explicit call to update any existing project (Updating DROP).

pip install -e ./drop

# update project directory
cd <path/to/project>
drop update

Installation without conda

The easiest way to ensure that all dependencies are installed is to install the bioconda package. Alternatively, DROP can be installed with pip. In this case the following dependencies must be met:

Note

If you are using an already existing R installation, make sure that the R and bioconductor versions match. Otherwise, use the newest versions of R and bioconductor.

At the first invocation, all the necessary R packages will be installed. As this is a lengthy process, it might be desirable to install them in advance.

# optional
Rscript <path/to/drop/repo>/drop/installRPackages.R drop/requirementsR.txt