SDePER: a hybrid machine learning and regression method for cell-type deconvolution of spatial barcoding-based transcriptomic data
Liu Y, Li N, Qi J, Xu G, Zhao J, Wang N, Huang X, Jiang W, Wei H, Justet A, Adams T, Homer R, Amei A, Rosas I, Kaminski N, Wang Z, Yan X. SDePER: a hybrid machine learning and regression method for cell-type deconvolution of spatial barcoding-based transcriptomic data. Genome Biology 2024, 25: 271. PMID: 39402626, PMCID: PMC11475911, DOI: 10.1186/s13059-024-03416-2.Peer-Reviewed Original ResearchSingle-cell transcriptomic analysis of human pleura reveals stromal heterogeneity and informs in vitro models of mesothelioma
Obacz J, Valer J, Nibhani R, Adams T, Schupp J, Veale N, Lewis-Wade A, Flint J, Hogan J, Aresu G, Coonar A, Peryt A, Biffi G, Kaminski N, Francies H, Rassl D, Garnett M, Rintoul R, Marciniak S. Single-cell transcriptomic analysis of human pleura reveals stromal heterogeneity and informs in vitro models of mesothelioma. European Respiratory Journal 2024, 63: 2300143. PMID: 38212075, PMCID: PMC10809128, DOI: 10.1183/13993003.00143-2023.Peer-Reviewed Original ResearchConceptsSingle-cell transcriptome atlasSingle-cell levelSingle-cell transcriptome analysisTranscriptome dataTranscriptomic atlasTranscriptomic characterisationMesothelial cellsCell atlasDevelopment of targeted therapiesMalignant mesothelial cellsModel of mesotheliomaUniversal fibroblastsIn vitro model