Skip to main content

MarcoPolo: a method to discover differentially expressed genes in single-cell RNA-seq data without depending on prior clustering

Project description

MarcoPolo: a method to discover differentially expressed genes in single-cell RNA-seq data without depending on prior clustering

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

marcopolo-pytorch-1.1.0.tar.gz (1.4 MB view details)

Uploaded Source

Built Distribution

marcopolo_pytorch-1.1.0-py3-none-any.whl (614.7 kB view details)

Uploaded Python 3

File details

Details for the file marcopolo-pytorch-1.1.0.tar.gz.

File metadata

  • Download URL: marcopolo-pytorch-1.1.0.tar.gz
  • Upload date:
  • Size: 1.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.11

File hashes

Hashes for marcopolo-pytorch-1.1.0.tar.gz
Algorithm Hash digest
SHA256 e9373191e1ab0fcf3a5c87cb0fba5d01ed3ab832fe2261a47a805b505b6450e9
MD5 36ced2962250fa6521d60611af0bab71
BLAKE2b-256 94a5a3e3c143aa5a8010aa1fcf96aa4df740a8c99d75e11b33d09c4a1e515205

See more details on using hashes here.

File details

Details for the file marcopolo_pytorch-1.1.0-py3-none-any.whl.

File metadata

File hashes

Hashes for marcopolo_pytorch-1.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 8436d953b8d9a38212ac267757711a7f3d36790016729d510e8b113f542c6db0
MD5 92d824998f6841f7d6857acb636c05af
BLAKE2b-256 cf9c8775e72be25c13d1d9905dae849f81090e4436d6252ed95fea0f47031681

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