Skip to main content

Geometric inference of cross-species transcriptome correspondence using Gromov–Wasserstein optimal transport.

Project description

Species-OT

Geometric inference of cross-species transcriptome correspondence using Gromov-Wasserstein optimal transport.

fig.png

Installation

$ pip install speciesot

Requirements

  • Python3

  • Apple Silicon or NVIDIA GPUs (recommended)

    Click here to learn how to utilize Apple Silicon's GPUs (official documentation).

Documentation

The tutorial is available here.

Preprint

Please see the following paper: Y. Tokuta et al. Geometric inference of cross-species transcriptome correspondence using Gromov-Wasserstein optimal transport. bioRxiv

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

speciesot-0.2.3.tar.gz (16.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

speciesot-0.2.3-py3-none-any.whl (16.6 kB view details)

Uploaded Python 3

File details

Details for the file speciesot-0.2.3.tar.gz.

File metadata

  • Download URL: speciesot-0.2.3.tar.gz
  • Upload date:
  • Size: 16.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.9.19 Darwin/24.6.0

File hashes

Hashes for speciesot-0.2.3.tar.gz
Algorithm Hash digest
SHA256 f0854435a6c7e045e82a8484e7f365a91cfb01de7bb5a4e0eddb0391570f3252
MD5 ed3185f177307f4669e451f45cf1aee3
BLAKE2b-256 aa6f6d682591483fbfca96b94e021f65a49d49f85f9ddcc43a59e45b5b194e21

See more details on using hashes here.

File details

Details for the file speciesot-0.2.3-py3-none-any.whl.

File metadata

  • Download URL: speciesot-0.2.3-py3-none-any.whl
  • Upload date:
  • Size: 16.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.9.19 Darwin/24.6.0

File hashes

Hashes for speciesot-0.2.3-py3-none-any.whl
Algorithm Hash digest
SHA256 7938bf1f6d80d65ff4caa1a7922ef0ee6e35e6b2279ec099ae8b1517043d9c29
MD5 6bafd00c9798c430d141eac2baee1919
BLAKE2b-256 3479bd8ca932ec8bd842cdc078461a75bf18875eb2cbb396105f6856c344bec8

See more details on using hashes here.

Supported by

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