Dysregulated ligand-receptor interactions from single-cell transcriptomics

Qi Liu, Chih Yuan Hsu, Jia Li, Yu Shyr

研究成果: Article同行評審

摘要

Motivation: Intracellular communication is crucial to many biological processes, such as differentiation, development, homeostasis and inflammation. Single-cell transcriptomics provides an unprecedented opportunity for studying cell-cell communications mediated by ligand-receptor interactions. Although computational methods have been developed to infer cell type-specific ligand-receptor interactions from one single-cell transcriptomics profile, there is lack of approaches considering ligand and receptor simultaneously to identifying dysregulated interactions across conditions from multiple single-cell profiles. Results: We developed scLR, a statistical method for examining dysregulated ligand-receptor interactions between two conditions. scLR models the distribution of the product of ligands and receptors expressions and accounts for inter-sample variances and small sample sizes. scLR achieved high sensitivity and specificity in simulation studies. scLR revealed important cytokine signaling between macrophages and proliferating T cells during severe acute COVID-19 infection, and activated TGF-β signaling from alveolar type II cells in the pathogenesis of pulmonary fibrosis.

原文English
頁(從 - 到)3216-3221
頁數6
期刊Bioinformatics
38
發行號12
DOIs
出版狀態Published - 2022 6月 15

All Science Journal Classification (ASJC) codes

  • 統計與概率
  • 生物化學
  • 分子生物學
  • 電腦科學應用
  • 計算機理論與數學
  • 計算數學

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