MetaTiME: Meta-components in Tumor immune MicroEnvironment

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MetaTiME learns data-driven, interpretable, and reproducible gene programs by integrating millions of single cells from hundreds of tumor scRNA-seq data. The idea is to learn a map of single-cell space with biologically meaningful directions from large-scale data, which helps understand functional cell states and transfers knowledge to new data analysis. MetaTiME provides pretrained meta-components (MeCs) to automatically annotate fine-grained cell states and plot signature continuum for new single-cells of tumor microenvironment.

Installation

Create a new virtual env and activate (optional)

python -m venv metatime-env; source metatime-env/bin/activate

Use pip to install

pip install metatime

Installation shall be in minutes .

Next we have a tutorial on applying MetaTiME on new TME scRNAseq data to annotate cell states, scoring signature continuum, and test differential signature activity.

Usage

MetaTiME-Annotator

• Use MetaTiME to automatically annotate cell states and map signatures
• [New] MetaTiME re-training pipeline at https://github.com/yi-zhang/MetaTiMEpretrain/

Interactive tutorial

Use MetaTiME to automatically annotate cell states and map signatures

Method

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Reference

Repo continously being improved! More details will be updated and suggested improvements welcome.

• [Paper at Nature Communications] (https://www.nature.com/articles/s41467-023-38333-8)
• Paper at bioRxiv

Training Datasets

Tumor scRNAseq Data for MetaTiME @ Zenodo

• A large collection of uniformly processed tumor single-cell RNA-seq.

• Includes raw data and MetaTiME score for the TME cells.

Dependency

• pandas
• scanpy
• anndata
• matplotlib
• adjustText
• leidenalg
• harmonypy

Dependency version tested:

• pandas==1.1.5
• scanpy==1.8.2
• anndata==0.8.0
• matplotlib==3.5.1
• adjustText==0.7.3
• leidenalg==0.8.3

Contact

Yi Zhang, Ph.D.

yiz [AT] ds.dfci.harvard.edu

Twitter | Website Research Fellow Department of Data Science Dana-Farber Cancer Institute Harvard University T.H. Chan School of Public Health