Accurate estimation of pathway activity in single cells for clustering and differential analysis

(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 2.
Figure 2.

SiPSiC-based clustering overcomes patient biases presented by gene-based clustering. (AC) UMAP projections based on gene expression (left) and hallmark pathway scores by SiPSiC (right). (A) Cells were clustered by Louvain algorithm according either to SiPSiC scores or to gene expression. UMAPs show cells colored by cluster. (B) Cells colored by patient identity. (C) Cells colored by malignant metamodule assignment.

This Article

  1. Genome Res. 34: 925-936

Preprint Server