Installation
Via pip
Python packages can be conveniently installed from the Python Package Index (PyPI) using pip install. CellBender is available on PyPI and can be installed via
$ pip install cellbender
If your machine has a GPU with appropriate drivers installed, it should be automatically detected, and the appropriate version of PyTorch with CUDA support should automatically be downloaded as a CellBender dependency.
We recommend installing CellBender in its own conda environment. This allows for easier installation and prevents conflicts with any other python packages you may have installed.
$ conda create -n cellbender python=3.7
$ conda activate cellbender
(cellbender) $ pip install cellbender
Installation from source
Create a conda environment and activate it:
$ conda create -n cellbender python=3.7
$ conda activate cellbender
Install the pytables module:
(cellbender) $ conda install -c anaconda pytables
Install pytorch via these instructions:
(cellbender) $ pip install torch
and ensure that your installation is appropriate for your hardware (i.e. that
the relevant CUDA drivers get installed and that torch.cuda.is_available()
returns True
if you have a GPU available.
Clone this repository and install CellBender (in editable -e
mode):
(cellbender) $ git clone https://github.com/broadinstitute/CellBender.git
(cellbender) $ pip install -e CellBender
Install a specific commit directly from GitHub
This can be achieved via
(cellbender) $ pip install --no-cache-dir -U git+https://github.com/broadinstitute/CellBender.git@<SHA>
where <SHA>
must be replaced by any reference to a particular git commit,
such as a tag, a branch name, or a commit sha.
Docker Image
A GPU-enabled docker image is available from the Google Container Registry (GCR) as:
us.gcr.io/broad-dsde-methods/cellbender:latest
Older versions are available at the same location, for example as
us.gcr.io/broad-dsde-methods/cellbender:0.2.0
Terra Workflow
For Terra users (or any other users of WDL workflows), the following WDL workflow is publicly available:
Some documentation for the WDL is available at the above link, and some is visible on github.