Identification of spatial homogeneous regions with concordex
Project description
concordex 1.0.2
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.
Installation
concordex
can be installed via pip
pip install git+https://github.com/pachterlab/concordex.git
Usage
After 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']
Citation
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}
}
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