{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["37(22)"],"submitter":["Nagai JS"],"funding":["German Research Foundation","German Ministry of Education and Science"],"pubmed_abstract":["<h4>Motivation</h4>Ligand-receptor (LR) network analysis allows the characterization of cellular crosstalk based on single cell RNA-seq data. However, current methods typically provide a list of inferred LR interactions and do not allow the researcher to focus on specific cell types, ligands or receptors. In addition, most of these methods cannot quantify changes in crosstalk between two biological phenotypes.<h4>Results</h4>CrossTalkeR is a framework for network analysis and visualization of LR interactions. CrossTalkeR identifies relevant ligands, receptors and cell types contributing to changes in cell communication when contrasting two biological phenotypes, i.e. disease versus homeostasis. A case study on scRNA-seq of human myeloproliferative neoplasms reinforces the strengths of Cros"],"journal":["Bioinformatics (Oxford, England)"],"pagination":["4263-4265"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9502146"],"repository":["biostudies-literature"],"pubmed_title":["CrossTalkeR: analysis and visualization of ligand-receptorne tworks."],"pmcid":["PMC9502146"],"pubmed_authors":["Schaub MT","Costa IG","Leimkuhler NB","Schneider RK","Nagai JS"],"additional_accession":[]},"is_claimable":false,"name":"CrossTalkeR: analysis and visualization of ligand-receptorne tworks.","description":"<h4>Motivation</h4>Ligand-receptor (LR) network analysis allows the characterization of cellular crosstalk based on single cell RNA-seq data. However, current methods typically provide a list of inferred LR interactions and do not allow the researcher to focus on specific cell types, ligands or receptors. In addition, most of these methods cannot quantify changes in crosstalk between two biological phenotypes.<h4>Results</h4>CrossTalkeR is a framework for network analysis and visualization of LR interactions. CrossTalkeR identifies relevant ligands, receptors and cell types contributing to changes in cell communication when contrasting two biological phenotypes, i.e. disease versus homeostasis. A case study on scRNA-seq of human myeloproliferative neoplasms reinforces the strengths of Cros","dates":{"release":"2021-01-01T00:00:00Z","publication":"2021 Nov","modification":"2025-04-19T03:32:29.786Z","creation":"2025-04-07T13:42:05.262Z"},"accession":"S-EPMC9502146","cross_references":{"pubmed":["35032393"],"doi":["10.1093/bioinformatics/btab370"]}}