Skip to main content

library for neighbor-dependent gene expression analysis

Project description

PyPI

CellNeighborEX: Deciphering Neighbor-Dependent Gene Expression from Spatial Transcriptomics Data

CellNeighborEX is a computational approach to identify genes up-regulated or down-regulated by immediate neighbors from spatial transcriptomics (ST) data at single cell or near cellular resolution. It works for both image-based and NGS-based ST data. For image-based ST data where exact cell locations are available, CellNeighborEX uses various algorithms including Delaunay triangulation and KNN to find immediate neighbors. For NGS-based ST data where exact cell locations are not available, CellNeighborEX leverages the mixture of transcriptomes in each spot. CellNeighborEX dissects cells or spots based on the cell types of the immediate neighbors. Carrying out differential expression analysis for the categorized cells or spots, CellNeighborEX detects neighbor-dependent genes. The expression of neighbor-dependent genes is validated in the spatial context.

The figure below shows the workflow of CellNeighborEX:

Fig 1

Installation

CellNeighborEX requires Python version >=3.8, <3.11. We recommend using conda environment to avoid dependency conflicts. The dependencies are listed in requirements.txt.

# Create conda environment “myenv”
conda create -n myenv python=3.10
conda activate myenv

# Navigate into the directory where requirements.txt is located. Then, install dependencies
pip install -r requirements.txt

# Install CellNeighborEX from PyPI
pip install CellNeighborEX

Python API documentation and tutorials

Please see this Read the Docs.

Citation

Hyobin Kim, Amit Kumar, Cecilia Lövkvist, António M. Palma, Patrick Martin, Junil Kim, Praveen Bhoopathi, Jose Trevino, Paul Fisher, Esha Madan, Rajan Gogna, and Kyoung Jae Won, CellNeighborEX: Deciphering Neighbor-Dependent Gene Expression from Spatial Transcriptomics Data, Molecular Systems Biology, 19(11), e11670, 2023. Link.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

CellNeighborEX-1.0.1.tar.gz (19.5 kB view details)

Uploaded Source

Built Distribution

CellNeighborEX-1.0.1-py3-none-any.whl (21.4 kB view details)

Uploaded Python 3

File details

Details for the file CellNeighborEX-1.0.1.tar.gz.

File metadata

  • Download URL: CellNeighborEX-1.0.1.tar.gz
  • Upload date:
  • Size: 19.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.12

File hashes

Hashes for CellNeighborEX-1.0.1.tar.gz
Algorithm Hash digest
SHA256 7870359eb01d1f2d9ab0bbdcfcb9687a35ba7b6299c00291a3edec97b553f3fa
MD5 a48dcb185b0d472359bac110d9905943
BLAKE2b-256 16cce0b7c923b837cec006b05e3696f6a27904accf6ca61f1ad48255d41cfd80

See more details on using hashes here.

File details

Details for the file CellNeighborEX-1.0.1-py3-none-any.whl.

File metadata

File hashes

Hashes for CellNeighborEX-1.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 6b6133d893af993881cba53a64e3eb72be7d24b2e4f3e30101fe1dd302112618
MD5 ccbbb0e1f088f4b8b097877f4ca9ae60
BLAKE2b-256 205733155bc7b5d3d2e298a2101d81b59b5980c5210bca6a876dbc5993ddd71a

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page