Skip to main content

Multi-modal spatial omics integration with views and combinations.

Project description

mmspao

Multi-modal spatial omics integration with views and combinations.

Experiments were executed on NVIDIA A40 of 46068MiB memory in linux with torch==2.1.0+cu121

Overview

mmspao is an innovative algorithm for multimodal spatial omics analysis, its core advantage is that it can seamlessly integrate transcriptome, proteome, epigenetics, metabolome and other data types. Through the unique modal interactive feature extraction and adaptive fusion mechanism, it can significantly improve the accuracy and biological interpretability of spatial domain recognition. The algorithm uses Kolmogorov-Arnold Network (KAN) to generate mode specific embedding, and constructs interactive features by calculating the outer product between modes. Finally, combined with Leiden clustering, it realizes the collaborative analysis of multimodal data.

install mmspao

pip install torch==2.1.0 --index-url https://download.pytorch.org/whl/cu121
pip install mmspao
# pip install numpy==1.26.4

Download files

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

Source Distribution

mmspao-1.0.0.tar.gz (7.7 kB view details)

Uploaded Source

Built Distribution

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

mmspao-1.0.0-py3-none-any.whl (7.4 kB view details)

Uploaded Python 3

File details

Details for the file mmspao-1.0.0.tar.gz.

File metadata

  • Download URL: mmspao-1.0.0.tar.gz
  • Upload date:
  • Size: 7.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.4

File hashes

Hashes for mmspao-1.0.0.tar.gz
Algorithm Hash digest
SHA256 f3db6b7058c041901b1a991b57865c685e6157838b3845575929747313f41afa
MD5 75bf9a414b97c9f7aacccf66c0439000
BLAKE2b-256 be68bc3ef7f90c6deec05b1524c4367eb44986c3c43f68e137adf83cb61880ee

See more details on using hashes here.

File details

Details for the file mmspao-1.0.0-py3-none-any.whl.

File metadata

  • Download URL: mmspao-1.0.0-py3-none-any.whl
  • Upload date:
  • Size: 7.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.4

File hashes

Hashes for mmspao-1.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 89b4520a9607cf4bc32e5046f3621ac45a012ad0b0ab817e078fde8993c62bc1
MD5 9de7844740e902802ebd7d358f128e55
BLAKE2b-256 f9ed7bca33a42f077bf5feeed9fe04e184ba60315c222de3fabffbb0a984c113

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