DROP is available on bioconda .
In case the conda channel priority is set to
strict, it should be reset to
We recommend using a dedicated conda environment (here:
drop_env) for installing drop.
conda create -n drop_env -c conda-forge -c bioconda drop
Installation time: ~ 10min
Test whether the pipeline runs through by setting up the demo dataset in an empty directory (e.g.
mkdir ~/drop_demo cd ~/drop_demo # demo will download the necessary data and pipeline files drop demo
The pipeline can be run using snakemake commands
snakemake -n # dryrun snakemake --cores 1
Initialize a project¶
The demo project can be modified to be used for a new project.
Alternatively, a new DROP project can be set up using
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 developer version of DROP can be found in the repository under the branch
Make sure that the Prerequisites are installed, preferably in a conda environment.
Then install DROP 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 useful 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).
The easiest way to ensure that all dependencies are installed is to install the bioconda package, as described above.
Once the environment is set up and installation was successful, other versions of drop can be installed with
overwriting the conda version of
DROP (see Other DROP versions).
Installation without conda¶
Alternatively, DROP can be installed without
conda. 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 first invocation, all necessary R packages will be installed with the first pipeline call. As this is a lengthy process, it might be desirable to install them in advance, if a local copy of the repository exists.
# optional Rscript <path/to/drop/repo>/drop/installRPackages.R drop/requirementsR.txt