Biostatistics Weekly Seminar

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. 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-b signaling from alveolar type II cells in the pathogenesis of pulmonary fibrosis.

An R Package scLR is freely available at https://github.com/cyhsuTN/scLR.

Zoom (Link to Follow)
08 June 2022
1:30pm