CarDEC (Count adapted regularized Deep Embedded Clustering) is a joint deep learning computational tool that is useful for analyses of single-cell RNA-seq data. CarDEC can be used to:
We described and introduced CarDEC in our methodological paper. To find code to reproduce the results we generated in that paper, please visit this separate github repository, which provides all code (including that for other methods) necessary to reproduce our results.
Recomended installation procedure is as follows.
$ conda create -n cardecenv
$ conda activate cardecenv
$ conda install python==3.7
$ conda install nb_conda_kernels
$ pip install CarDEC
Now, to use CarDEC, always make sure you activate the environment in terminal first ("conda activate cardecenv"). And then run jupyter notebook. When you create a notebook to run CarDEC, make sure the active kernel is switched to "cardecenv"
A tutorial jupyter notebook, together with a dataset, is publicly downloadable.
Installation on MacOS should be smooth. If installing on Windows Subsystem for Linux (WSL), the user must properly configure their g++ compiler to ensure that the louvain package can be built during installation. If the compiler is not properly configured, the user may encounter a following deprecation error similar to the following.
"DEPRECATION: Could not build wheels for louvain which do not use PEP 517. pip will fall back to legacy 'setup.py install' for these. pip 21.0 will remove support for this functionality. A possible replacement is to fix the wheel build issue reported above."
To fix this error, try to install the libxml2-dev package.