Skip to main content

Add a short description here!

Project description

PyPI-Server Unit tests DOI

Decima

Introduction

Decima is a Python library to train sequence models on single-cell RNA-seq data.

Figure

Weights

Weights of the trained Decima models (4 replicates) are now available at https://zenodo.org/records/15092691. See the tutorial for how to load and use these.

Preprint

Please cite https://www.biorxiv.org/content/10.1101/2024.10.09.617507v3. Also see https://github.com/Genentech/decima-applications for all the code used to train and apply models in this preprint.

Requirements

Decima has been tested on Ubuntu 24.04.3 and MacOS 15.6.1 using Python 3.9-3.12.

Installation

Install the package from PyPI,

pip install decima

Or if you want to be on the cutting edge,

pip install git+https://github.com/genentech/decima.git@main

Typical installation time including all dependencies is under 10 minutes.

Tutorials

See the tutorials for instructions, including how to train your own Decima model with an example dataset.

Note

This project has been set up using BiocSetup and PyScaffold.

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

decima-0.6.2.tar.gz (2.1 MB view details)

Uploaded Source

Built Distribution

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

decima-0.6.2-py3-none-any.whl (100.8 kB view details)

Uploaded Python 3

File details

Details for the file decima-0.6.2.tar.gz.

File metadata

  • Download URL: decima-0.6.2.tar.gz
  • Upload date:
  • Size: 2.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for decima-0.6.2.tar.gz
Algorithm Hash digest
SHA256 e49f57a06888b1e26577c62f34c0f91ca389115a29c3567b42de045c0644452c
MD5 53ef74a2c96d3d945a756d8d99b52b51
BLAKE2b-256 893c66ebbdb71d5be990d7cba8d26dc671bf4fcb2fe0312ef251e89ec2ef52c8

See more details on using hashes here.

Provenance

The following attestation bundles were made for decima-0.6.2.tar.gz:

Publisher: publish-pypi.yml on Genentech/decima

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file decima-0.6.2-py3-none-any.whl.

File metadata

  • Download URL: decima-0.6.2-py3-none-any.whl
  • Upload date:
  • Size: 100.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for decima-0.6.2-py3-none-any.whl
Algorithm Hash digest
SHA256 eeba3e57536fdc4c6b9123139ad01dfe4de2efc8d2671441cf9cbb522b7c9a29
MD5 2270c3d596516d8f1dc2ef5ae6647aae
BLAKE2b-256 c63f2e3e9141ed0371296f642cab796df94bcc455ed5a01b76c2f298ac9d3c62

See more details on using hashes here.

Provenance

The following attestation bundles were made for decima-0.6.2-py3-none-any.whl:

Publisher: publish-pypi.yml on Genentech/decima

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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