LRLoop: a method to predict feedback loops in cell–cell communication

作者：Ying Xin, Pin Lyu, Junyao Jiang, Feng‐Quan Zhou, Jie Wang, Seth Blackshaw, Jiang Qian · 发表于：Bioinformatics · 年份：2022 · DOI：10.1093/bioinformatics/btac447 · 被引用次数：36 · 研究领域：Single-cell and spatial transcriptomics、Bioinformatics and Genomic Networks、Gene Regulatory Network Analysis

MOTIVATION: Intercellular communication (i.e. cell-cell communication) plays an essential role in multicellular organisms coordinating various biological processes. Previous studies discovered that feedback loops between two cell types are a widespread and vital signaling motif regulating development, regeneration and cancer progression. While many computational methods have been developed to predict cell-cell communication based on gene expression datasets, these methods often predict one-directional ligand-receptor interactions from sender to receiver cells and are not suitable to identify feedback loops. RESULTS: Here, we describe ligand-receptor loop (LRLoop), a new method for analyzing cell-cell communication based on bi-directional ligand-receptor interactions, where two pairs of ligand-receptor interactions are identified that are responsive to each other and thereby form a closed feedback loop. We first assessed LRLoop using bulk datasets and found our method significantly reduces the false positive rate seen with existing methods. Furthermore, we developed a new strategy to assess the performance of these methods in single-cell datasets. We used the between-tissue interactions as an indicator of potential false-positive prediction and found that LRLoop produced a lower fraction of between-tissue interactions than traditional methods. Finally, we applied LRLoop to the single-cell datasets obtained from retinal development. We discovered many new bi-directional ligand-...