SIMBA: SIngle-cell eMBedding Along with features

Website: https://simba-bio.readthedocs.io

Preprint: Huidong Chen, Jayoung Ryu, Michael E. Vinyard, Adam Lerer & Luca Pinello. "SIMBA: SIngle-cell eMBedding Along with features. bioRxiv, 2021.10.17.464750v1 (2021)."

This branch supports marker significance calculation and continuous edge weights. For the relevant documentation, see the updated tutorial.

To install simba from this branch:

conda create -n env_simba_dev jupyter pytorch pybedtools -y
pip install 'simba @ git+https://github.com/pinellolab/simba@dev'

To enable the k-mer and TF analyses please install these additional dependencies(optional):

conda install r-essentials r-optparse bioconductor-jaspar2020 bioconductor-biostrings bioconductor-tfbstools bioconductor-motifmatchr bioconductor-summarizedexperiment r-doparallel bioconductor-rhdf5 bioconductor-hdf5array

Documentation for the continuous edge weight can be found here. Documentation for the marker feature significance calculation can be found here.