DROP is available on bioconda .
In case the conda channel priority is set to
strict, it should be reset to
conda config --set channel_priority true
We recommend using a dedicated conda environment (here:
drop_env) for installing DROP.
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
mamba env create -f DROP_1.3.3.yaml
Installation time: ~ 10min
We can test whether the pipeline runs through by setting up the demo dataset in an empty directory (e.g.
conda activate drop_env
# this command will download the necessary data and pipeline files
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
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
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 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
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
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:
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.
Rscript <path/to/drop/repo>/drop/installRPackages.R drop/requirementsR.txt