Dysregulated ligand-receptor interactions from single-cell transcriptomics.
Bioinformatics
; 38(12): 3216-3221, 2022 Jun 13.
Article
in English
| MEDLINE | ID: covidwho-1815994
ABSTRACT
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-ß signaling from alveolar type II cells in the pathogenesis of pulmonary fibrosis. AVAILABILITY AND IMPLEMENTATION scLR is freely available at https//github.com/cyhsuTN/scLR. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Transcriptome
/
COVID-19
Type of study:
Diagnostic study
Limits:
Humans
Language:
English
Journal:
Bioinformatics
Journal subject:
Medical Informatics
Year:
2022
Document Type:
Article
Affiliation country:
Bioinformatics
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