2024
Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data
Dai R, Chu T, Zhang M, Wang X, Jourdon A, Wu F, Mariani J, Vaccarino F, Lee D, Fullard J, Hoffman G, Roussos P, Wang Y, Wang X, Pinto D, Wang S, Zhang C, consortium P, Chen C, Liu C. Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data. Science Advances 2024, 10: eadh2588. PMID: 38781336, PMCID: PMC11114236, DOI: 10.1126/sciadv.adh2588.Peer-Reviewed Original ResearchConceptsHuman brain transcriptome dataBrain transcriptomic dataRNA-seqTranscriptome dataCell-type gene expressionGene expressionCell-type proportionsSingle-cell dataMultiple brain disordersBrain cell typesCell deconvolution methodsPostmortem brainsRNA sequencingBrain disordersBrain developmentSchizophreniaEQTLAlzheimer's diseaseCell typesOrganoid samplesBrainBiological applications
2012
Modeling human cortical development in vitro using induced pluripotent stem cells
Mariani J, Simonini MV, Palejev D, Tomasini L, Coppola G, Szekely AM, Horvath TL, Vaccarino FM. Modeling human cortical development in vitro using induced pluripotent stem cells. Proceedings Of The National Academy Of Sciences Of The United States Of America 2012, 109: 12770-12775. PMID: 22761314, PMCID: PMC3411972, DOI: 10.1073/pnas.1202944109.Peer-Reviewed Original ResearchConceptsHuman brain developmentHuman induced pluripotent stem cellsLayer-specific cortical neuronsBrain developmentHuman cerebral cortexHuman cortical developmentStem cellsPluripotent stem cellsCerebral cortexCortical neuronsCortical developmentCNS regionsRadial gliaCortical wallDorsal telencephalonEmbryonic telencephalonGene expression profilesInduced pluripotent stem cellsIntermediate progenitorsTelencephalic developmentTelencephalonExpression profilesTranscriptional programsCellsGlia