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 ResearchComputationally inferred cell-type specific epigenome-wide DNA methylation analysis unveils distinct methylation patterns among immune cells for HIV infection in three cohorts
Zhang X, Hu Y, Vandenhoudt R, Yan C, Marconi V, Cohen M, Wang Z, Justice A, Aouizerat B, Xu K. Computationally inferred cell-type specific epigenome-wide DNA methylation analysis unveils distinct methylation patterns among immune cells for HIV infection in three cohorts. PLOS Pathogens 2024, 20: e1012063. PMID: 38466776, PMCID: PMC10957090, DOI: 10.1371/journal.ppat.1012063.Peer-Reviewed Original ResearchCD4+ T cellsEpigenome-wide association studiesPeripheral blood mononuclear cellsHIV infectionHIV pathogenesisT cellsCpG sitesNatural killer (NK) cellsCell typesAssociated with HIV infectionCD8+ T cellsMethylation patternsCpG methylationDNA methylationEpigenome-wide DNA methylation analysisBlood mononuclear cellsImmune cell typesDifferentially methylated CpG sitesUnique CpG sitesDifferential CpG methylationDNA methylation analysisSignificant CpG sitesArray-based methodsGene set enrichment analysisComputational deconvolution methods