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10.1093/bioinformatics/btac294 http://scihub22266oqcxt.onion/10.1093/bioinformatics/btac294 35482476!9191214!35482476     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Bioinformatics 2022 ; 38 (12): 3216-3221 Nephropedia Template TP {{tp|p=35482476|t=2022. Dysregulated ligand-receptor interactions from single-cell transcriptomics |pdf=|usr=}}{{35482476}} gab.com Text Dysregulated ligand-receptor interactions from single-cell transcriptomics JO: Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=35482476 #FOAvip 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-beta 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. Twit Text FOAVip Dysregulated ligand-receptor interactions from single-cell transcriptomics ????Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=35482476 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=35482476 #FOAvip English Wikipedia <ref>{{Cite pmid|35482476}}</ref> Dysregulated ligand-receptor interactions from single-cell transcriptomics #MMPMID35482476 Liu Q; Hsu CY; Li J; Shyr Y Bioinformatics 2022[Jun]; 38 (12): 3216-3221 PMID35482476show ga 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-beta 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. |*COVID-19[MESH] |*Transcriptome[MESH] |Humans[MESH] |Ligands[MESH]Dysregulated ligand-receptor interactions from single-cell transcripto(epmc).pdf DeepDyve Pubget Overpricing