Screening cell–cell communication in spatial transcriptomics via collective optimal transport

Spatial transcriptomic technologies and spatially annotated single-cell RNA sequencing datasets provide unprecedented opportunities to dissect cell-cell communication (CCC). However, incorporation of the spatial information and complex biochemical processes required in the reconstruction of CCC remains a major challenge. Here, we present COMMOT (COMMunication analysis by Optimal Transport) to infer CCC in spatial transcriptomics, which accounts for the competition between different ligand and receptor species as well as spatial distances between cells. A collective optimal transport method is developed to handle complex molecular interactions and spatial constraints. Furthermore, we introduce downstream…

• NS
  National Science Foundation

  Awards: DMS1763272, CBET2134916
• SF
  Simons Foundation

  Awards: 357963, U01AR073159, 594598
• NC
  North Carolina State University
• NI
  National Institutes of Health

  Awards: R01DE030565, 594598, AN-0000000062, R01AR079150, DMS1763272, U01AR073159
• UO
  University of California, Irvine
• DO
  Division of Chemical, Bioengineering, Environmental, and Transport Systems

  Award: CBET2134916