Detection and analysis of complex structural variation in human genomes across populations and in brains of donors with psychiatric disorders
Zhou B, Arthur J, Guo H, Kim T, Huang Y, Pattni R, Wang T, Kundu S, Luo J, Lee H, Nachun D, Purmann C, Monte E, Weimer A, Qu P, Shi M, Jiang L, Yang X, Fullard J, Bendl J, Girdhar K, Kim M, Chen X, Consortium P, Greenleaf W, Duncan L, Ji H, Zhu X, Song G, Montgomery S, Palejev D, Dohna H, Roussos P, Kundaje A, Hallmayer J, Snyder M, Wong H, Urban A. Detection and analysis of complex structural variation in human genomes across populations and in brains of donors with psychiatric disorders. Cell 2024, 187: 6687-6706.e25. PMID: 39353437, DOI: 10.1016/j.cell.2024.09.014.Peer-Reviewed Original ResearchComplex structural variationsNatural human genetic variationHuman genetic variationCell type-specific expressionHuman-specific evolutionDifferential gene expressionStructural variationsContinental populationsChromatin accessibilityHuman genomeGenetic variationNeural genesGenomeGene expressionRisk allelesMolecular etiologyCell typesGenesPostmortem brainsChromatinLociAllelesMachine-learning-based methodsMultiomicsBrain regionsPrioritizing disease-related rare variants by integrating gene expression data
Guo H, Urban A, Wong H. Prioritizing disease-related rare variants by integrating gene expression data. PLOS Genetics 2024, 20: e1011412. PMID: 39348415, PMCID: PMC11466430, DOI: 10.1371/journal.pgen.1011412.Peer-Reviewed Original ResearchConceptsGene expression dataRare variantsExpression dataRare variant association methodsExcess of rare variantsImpact of rare variantsContext of human diseaseHuman genetic variationGenetic variationGene expressionComplex diseasesHuman diseasesGenesMolecular mechanismsFunctional consequencesRare variant typesAlzheimer's diseaseVariant typeVariantsAssociation methodStatistical frameworkSimulation studySample sizeOmicsAlzheimerSingle-cell genomics and regulatory networks for 388 human brains
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