omicverse 1.5.8

OmicVerse: A single pipeline for exploring the entire transcriptome universe

OmicVerse is the fundamental package for multi omics included bulk and single cell analysis with Python. For more information, please read our paper: OmicVerse: A single pipeline for exploring the entire transcriptome universe

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.

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 “interrupted” cells in the original scRNA-seq data.

Directory structure

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

Where to get it

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.

Usage

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

Data Framework

• pandas
• anndata
• numpy
• mudata

Reference

• [1] Scanpy was originally published in Genome biology
• [2] dynamicTreeCut was originally published in Bioinformatics
• [3] scDrug was originally published in Computational and Structural Biotechnology Journal
• [4] MOFA was originally published in Genome Biology
• [5] COSG was originally published in Briefings in Bioinformatics
• [6] CellphoneDB was originally published in Nature
• [7] AUCell was originally available in Bioconductor, and we use the script of Pyscenic to instead.
• [8] Bulk2Space was originally published in Nature Communications
• [9] SCSA was originally published in Front Genet
• [10] WGCNA was originally avaliable in BMC Bioinformatics
• [11] VIA was originally published in Nature Communications
• [12] pyDEseq2 was originally published in biorxiv
• [13] NOCD was originally avaliable in Deep Learning on Graphs Workshop, KDD
• [14] SIMBA was originally published in Nature Methods
• [15] GLUE was originally published in Nature Biotechnology
• [16] MetaTiME was originally published in Nature Communications
• [17] TOSICA was originally published in Nature Communications
• [18] Harmony was originally published in Nature Methods
• [19] Scanorama was originally published in Nature Biotechnology
• [20] Combat was originally published in biorxiv
• [21] TAPE was originally published in Nature Communications
• [22] SEACells was originally published in Nature Biotechnology
• [23] Palantir was originally published in Nature Biotechnology
• [24] STAGATE was originally published in Nature Communications
• [25] scVI was originally published in Nature Biotechnology
• [26] MIRA was originally published in Nature Methods
• [27] Tangram was originally published in Nature Methods
• [28] STAligner was originally published in Nature Computational Science
• [29] CEFCON was originally published in Nature Communications
• [30] PyComplexHeatmap was originally published in iMeta

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.

Contact

• Zehua Zeng ([e-mail] or [e-mail])
• Lei Hu ([e-mail])

Developer Guild

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

Acknowledgements

We would like to thank the following WeChat Official Accounts for promoting Omicverse.

Other

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