A generalization of t-SNE and UMAP to single-cell multimodal omics

Genome Biology

Stefan Canzar¹  Van Hoan Do¹ 

[1] Gene Center, Ludwig-Maximilians-Universität München, Feodor-Lynen-Str. 25, Munich, Germany;

关键词: Data visualization;    Single-cell sequencing;    Multimodal omics;    t-SNE;    UMAP;    RNA velocity;    Protein velocity;   

DOI  :  10.1186/s13059-021-02356-5

来源: Springer

【 摘 要 】

Emerging single-cell technologies profile multiple types of molecules within individual cells. A fundamental step in the analysis of the produced high-dimensional data is their visualization using dimensionality reduction techniques such as t-SNE and UMAP. We introduce j-SNE and j-UMAP as their natural generalizations to the joint visualization of multimodal omics data. Our approach automatically learns the relative contribution of each modality to a concise representation of cellular identity that promotes discriminative features but suppresses noise. On eight datasets, j-SNE and j-UMAP produce unified embeddings that better agree with known cell types and that harmonize RNA and protein velocity landscapes.

【 授权许可】

CC BY