The goal of concordex is to identify spatial homogeneous regions (SHRs) as defined in the recent manuscript, “Identification of spatial homogenous regions in tissues with concordex”. Briefly, SHRs are are domains that are homogeneous with respect to cell type composition. concordex relies on the the k-nearest-neighbor (kNN) graph to representing similarities between cells and uses common clustering algorithms to identify SHRs.
concordex can be installed via pip
pip install concordex.... and from Github
pip install git+https://github.com/pachterlab/concordex.gitAfter installing, concordex can be run as follows:
import scanpy as sc
from concordex.tools import calculate_concordex
ad = sc.datasets.pbmc68k_reduced()
# Compute concordex with discrete labels
calculate_concordex(ad, 'louvain', n_neighbors=10)
# Neighborhood consolidation information is stored in `adata.obsm`
ad.obsm['nbc'][:3]
# The column names are stored in `adata.uns`
ad.uns['nbc_params']['nbc_colnames']
If you’d like to use the concordex package in your research, please
cite our recent bioRxiv preprint:
Jackson, K.; Booeshaghi, A. S.; Gálvez-Merchán, Á.; Moses, L.; Chari, T.; Kim, A.; Pachter, L. Identification of spatial homogeneous regions in tissues with concordex. bioRxiv (Cold Spring Harbor Laboratory) 2023. https://doi.org/10.1101/2023.06.28.546949.
@article {Jackson2023.06.28.546949,
author = {Jackson, Kayla C. and Booeshaghi, A. Sina and G{'a}lvez-Merch{'a}n, {'A}ngel and Moses, Lambda and Chari, Tara and Kim, Alexandra and Pachter, Lior},
title = {Identification of spatial homogeneous regions in tissues with concordex},
year = {2024},
doi = {10.1101/2023.06.28.546949},
publisher = {Cold Spring Harbor Laboratory},
URL = {<https://www.biorxiv.org/content/early/2024/07/18/2023.06.28.546949>},
journal = {bioRxiv}
}