An AI-driven method for enhanced cellular organizational map in spatial transcriptomics

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for AbbyWY from gravatar.com AbbyWY

Unverified details

These details have not been verified by PyPI
Project links
GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Meta

License: MIT

Author: Ying Wu

Project description

Here we propose STASCAN, which both gene expression and the morphological information are simultaneously utilized to improve the cellular resolution of captured domains and even gap regions. Besides, STASCAN is further designed to enable cell-type predictions at subdivide-spot resolution and construction of the 3D spatial cell map from histology images alone.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for AbbyWY from gravatar.com AbbyWY

Unverified details

These details have not been verified by PyPI
Project links
GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Meta

License: MIT

Author: Ying Wu


Release history Release notifications | RSS feed

This version

1.1.0

1.0.0

Download files

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

Source Distribution

STASCAN-1.1.0.tar.gz (15.6 kB view hashes)

Uploaded Source

Built Distribution

STASCAN-1.1.0-py3-none-any.whl (22.0 kB view hashes)

Uploaded Python 3

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