STACCato: A tensor-based regression model for identifying condition-related cell-cell communication from single-cell RNA-seq data
By
Jingjing Yang2 Send email to [email protected]
Summary
This article introduces STACCato, a tensor-based regression model designed to identify condition-related cell-cell communication (CCC) events from single-cell RNA sequencing (scRNA-seq) data. CCC events involve ligand-receptor interactions between sender and receiver cells that coordinate physiological functions. The authors present STACCato as a method that accounts for confounders and provides rigorous inference of condition-related CCC events. The paper demonstrates the model's effectiveness using both simulated and real scRNA-seq data, addressing a key challenge in computational biology of distinguishing condition-specific signaling from background noise.
Source
bskySTACCato: A tensor-based regression model for identifying condition-related cell-cell communication from single-cell RNA-seq datacell.comKey quotes
· 4 pulledCell-cell communication (CCC) involves cells exchanging signals to coordinate physiological and developmental functions in multicellular organisms.
The study of CCC events, which involve interactions between a ligand from a sender cell and a receptor from a receiver cell, is important for elucidating biological processes, exploring disease mechanisms, and inspiring advancements in drug discovery.
We introduce STACCato, a tensor-based regression model that assesses condition-related CCC events, accounting for confounders.
We show that STACCato provides rigorous inference of such events using simulated and real scRNA-seq data.
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