Accurate integration of multiple heterogeneous single-cell RNA-seq data sets by learning contrastive biological variation

(Downloading may take up to 30 seconds. If the slide opens in your browser, select File -> Save As to save it.)

Click on image to view larger version.

Figure 6.
Figure 6.

scInt reveals inflammatory-related mechanisms in the COVID-19 data. (A,B) UMAP visualizations of the COVID-19 PBMC data in the raw data (A) and scInt-integrated data (B). Cells are colored by batches and COVID-19 stage conditions. (C) UMAP visualizations of the scInt-integrated data. Cells are colored by identified cell types. (D) Stacked violin plot of the top-important marker gene expression for each cell type. (E) Overlay of the expression patterns of the cytokine storm-related and inflammation-related chemokine genes in the CD14+ monocytes. (F) The top 10 enriched GO biological processes associated with cluster 9 and other CD14+ monocytes.

This Article

  1. Published in Advance June 12, 2023, doi: 10.1101/gr.277522.122 Genome Res. 33: 750-762

Preprint Server



Current Issue

  1. January 2026, 36 (1)
  1. Current Issue
  1. Alert me to new issues of Genome Research