Computational suite for studying cell-cell interactions and communication

The suite cell2cell includes two main sub-tools:

• The regular cell2cell, which includes the main approaches described in our review.
• Tensor-cell2cell, a novel method that uses tensor factorization to deconvolve patterns of cell-cell communication across multiple cellular contexts (e.g., time points, disease states, cellular location, patients, etc.), as described in our research article.

---

Tutorials

cell2cell Examples

• Step-by-step Pipeline
• Interaction Pipeline for Bulk Data
• Interaction Pipeline for Single-Cell Data
• Whole Body of C. elegans

Tensor-cell2cell Examples

• Obtaining patterns of cell-cell communication
• Downstream 1: Factor-specific analyses
• Downstream 2: Patterns to functions (GSEA)
• Tensor-cell2cell in Google Colab (GPU)
• Communication patterns in Spatial Transcriptomics

Reproducible runs of the analyses in the Tensor-cell2cell paper are available at CodeOcean.com

LIANA & Tensor-cell2cell

Explore our tutorials for using Tensor-cell2cell with LIANA at ccc-protocols.readthedocs.io.

Project link: https://earmingol.github.io/cell2cell/

• Python
• RNA-seq
• single-cell
• transcriptomics
• tools
• cell-cell interactions
• cell-cell communication