Installation

A step-by-step guide

The easiest way to prepare a python environment for SSAM is using conda. Keeping python projects in isolated environments prevents dependency version conflicts or conflicts with your OS installation of python which usually depends on older versions incompatible with current scientific packages.

Create your environment:

conda create -n ssam python=3.6

Remember to activate before using it:

conda activate ssam

Now we use conda to install some dependencies into our ssam environment:

conda install gxx_linux-64=7.3.0 numpy=1.19.2 pip R=3.6 pyarrow=0.15.1

Now we can install the R packages sctransform and feather. Open R and type:

install.packages("sctransform")
install.packages("feather")

Finally we switch to pip:

pip install git+https://github.com/HiDiHlabs/ssam.git

Next we can download and prepare our data.

SSAM’s source code

In case you want to work with SSAM’s source code, it is also hosted on github.