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.

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.

pandas

anndata

numpy

mudata

---

The table contains the tools have been published

Scanpy 📦 📖	dynamicTreeCut 📦 📖	scDrug 📦 📖	MOFA 📦 📖	COSG 📦 📖	CellphoneDB 📦 📖
AUCell 📦 📖	Bulk2Space 📦 📖	SCSA 📦 📖	WGCNA 📦 📖	VIA 📦 📖	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 📦 📖

---

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

• Zehua Zeng ([email protected] or [email protected])
• Lei Hu ([email protected])

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.

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.

8 Other

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

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