Skip to main content

OmicVerse: A single pipeline for exploring the entire transcriptome universe

Project description

pypi-badge Documentation Status pypiDownloads condaDownloads License:GPL scverse Pytest Docker Pulls

OmicVerse is the fundamental package for multi omics included bulk ,single cell and spatial RNA-seq analysis with Python. For more information, please read our paper: OmicVerse: a framework for bridging and deepening insights across bulk and single-cell sequencing

[!IMPORTANT]

Star Us, You will receive all release notifications from GitHub without any delay ~ ⭐️

If you like OmicVerse and want to support our mission, please consider making a 💗donation to support our efforts.

Star History

1 Introduction

The original name of the omicverse was Pyomic, but we wanted to address a whole universe of transcriptomics, so we changed the name to OmicVerse, it aimed to solve all task in RNA-seq.

[!NOTE] BulkTrajBlend algorithm in OmicVerse that combines Beta-Variational AutoEncoder for deconvolution and graph neural networks for overlapping community discovery to effectively interpolate and restore the continuity of "omission" cells in the original scRNA-seq data.

omicverse-light omicverse-dark

2 Directory structure

.
├── omicverse                  # Main Python package
├── omicverse_guide            # Documentation files
├── sample                     # Some test data
├── LICENSE
└── README.md

3 Getting Started

OmicVerse can be installed via conda or pypi and you need to install pytorch at first. Please refer to the installation tutorial for more detailed installation steps and adaptations for different platforms (Windows, Linux or Mac OS).

You can use conda install omicverse -c conda-forge or pip install -U omicverse for installation.

Please checkout the documentations and tutorials at omicverse page or omicverse.readthedocs.io.

4 Data Framework and Reference

The omicverse is implemented as an infrastructure based on the following four data structures.


The table contains the tools have been published

Scanpy
📦 📖
dynamicTreeCut
📦 📖
scDrug
📦 📖
MOFA
📦 📖
COSG
📦 📖
CellphoneDB
📦 📖
AUCell
📦 📖
Bulk2Space
📦 📖
SCSA
📦 📖
WGCNA
📦 📖
StaVIA
📦 📖
pyDEseq2
📦 📖
NOCD
📦 📖
SIMBA
📦 📖
GLUE
📦 📖
MetaTiME
📦 📖
TOSICA
📦 📖
Harmony
📦 📖
Scanorama
📦 📖
Combat
📦 📖
TAPE
📦 📖
SEACells
📦 📖
Palantir
📦 📖
STAGATE
📦 📖
scVI
📦 📖
MIRA
📦 📖
Tangram
📦 📖
STAligner
📦 📖
CEFCON
📦 📖
PyComplexHeatmap
📦 📖
STT
📦 📖
SLAT
📦 📖
GPTCelltype
📦 📖
PROST
📦 📖
CytoTrace2
📦 📖
GraphST
📦 📖
COMPOSITE
📦 📖
mellon
📦 📖
starfysh
📦 📖
COMMOT
📦 📖
flowsig
📦 📖
pyWGCNA
📦 📖
CAST
📦 📖
scMulan
📦 📖
cellANOVA
📦 📖
BINARY
📦 📖
GASTON
📦 📖
pertpy
📦 📖
inmoose
📦 📖
memento
📦 📖
GSEApy
📦 📖
marsilea
📦 📖
scICE
📦 📖
sude
📦 📖
GeneFromer
📦 📖
scGPT
📦 📖
scFoundation
📦 📖
UCE
📦 📖
CellPLM
📦 📖
kb_python
📦 📖
Scaden
📦 📖
BayesPrime
📦 📦 📖
InstaPrime
📦 📖

Included Package not published or preprint

  • [1] Cellula is to provide a toolkit for the exploration of scRNA-seq. These tools perform common single-cell analysis tasks
  • [2] pegasus is a tool for analyzing transcriptomes of millions of single cells. It is a command line tool, a python package and a base for Cloud-based analysis workflows.
  • [3] cNMF is an analysis pipeline for inferring gene expression programs from single-cell RNA-Seq (scRNA-Seq) data.

5 Contact

6 Developer Guild and Contributing

If you would like to contribute to omicverse, please refer to our developer documentation.




[!IMPORTANT]
We would like to thank the following WeChat Official Accounts for promoting Omicverse.

linux linux

7 Citation

If you use omicverse in your work, please cite the omicverse publication as follows:

OmicVerse: a framework for bridging and deepening insights across bulk and single-cell sequencing

Zeng, Z., Ma, Y., Hu, L. et al.

Nature Communication 2024 Jul 16. doi: 10.1038/s41467-024-50194-3.

Here are some other related packages, feel free to reference them if you use them!

CellOntologyMapper: Consensus mapping of cell type annotation

Zeng, Z., Wang, X., Du, H.

bioRxiv 2025 Jun 20. doi: 10.1101/2025.06.10.658951.

8 Other

If you would like to sponsor the development of our project, you can go to the afdian website (https://ifdian.net/a/starlitnightly) and sponsor us.

Copyright © 2024 112 Lab.
This project is GPL3.0 licensed.

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

omicverse-1.7.8.tar.gz (11.8 MB view details)

Uploaded Source

Built Distribution

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

omicverse-1.7.8-py3-none-any.whl (12.5 MB view details)

Uploaded Python 3

File details

Details for the file omicverse-1.7.8.tar.gz.

File metadata

  • Download URL: omicverse-1.7.8.tar.gz
  • Upload date:
  • Size: 11.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.18

File hashes

Hashes for omicverse-1.7.8.tar.gz
Algorithm Hash digest
SHA256 d3b8a94453da27388ee218b9cce4972c0782da6d278d05fc2d5c907f74fc724b
MD5 97e894a223eb648a88cd6972c6d8f846
BLAKE2b-256 063b949ed9e2c94c161f1032d824470ecd3309e26a0502b4107e950e42b92fc3

See more details on using hashes here.

File details

Details for the file omicverse-1.7.8-py3-none-any.whl.

File metadata

  • Download URL: omicverse-1.7.8-py3-none-any.whl
  • Upload date:
  • Size: 12.5 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.18

File hashes

Hashes for omicverse-1.7.8-py3-none-any.whl
Algorithm Hash digest
SHA256 30887434eaaecf2794e66d5a600c05208751f2e102967ed5b153a582be9934ec
MD5 8d764a6aa42ec4588632b5fe3ae88495
BLAKE2b-256 168c934f87e7e7d6a16784050cb90bc171a72666822b883ea5bc51d8795c1abe

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