HEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics
Yuan X, Ma Y, Gao R, Cui S, Wang Y, Fa B, Ma S, Wei T, Ma S, Yu Z. HEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics. Nature Communications 2024, 15: 5700. PMID: 38972896, PMCID: PMC11228050, DOI: 10.1038/s41467-024-49846-1.Peer-Reviewed Original ResearchConceptsSpatially variable genesVariable genesSpatial expression patternsSpatial transcriptomics technologiesSpatial transcriptomics researchTranscriptome researchTranscriptomic technologiesBiological functionsExpression patternsSpatial transcriptomicsGenesState-of-the-art methodsColorectal cancer dataA generalized calibrated Bayesian hierarchical modeling approach to basket trials with multiple endpoints
Chi X, Yuan Y, Yu Z, Lin R. A generalized calibrated Bayesian hierarchical modeling approach to basket trials with multiple endpoints. Biometrical Journal 2024, 66: e2300122. PMID: 38368277, PMCID: PMC11323483, DOI: 10.1002/bimj.202300122.Peer-Reviewed Original ResearchMeSH KeywordsBayes TheoremComputer SimulationHumansMolecular Targeted TherapyNeoplasmsResearch DesignConceptsBayesian hierarchical modeling approachShrinkage parameterTheoretical propertiesPhase II basket trialBasket trialsSimulation studyHierarchical modelHierarchical modeling approachFunctional formGeneral hierarchical modelEfficacy endpointLatent variable approachApproach yieldsRisk-benefit profileVariable approachImmunotherapy agentsTumor responseGeneralizationTargeted therapyCancer subtypesMultiple cancer subtypesTreatment effectsMonitoring procedures