Yuhan Xie
Postdoctoral AssociateAbout
Research
Publications
2024
Statistical methods for assessing the effects of de novo variants on birth defects
Xie Y, Wu R, Li H, Dong W, Zhou G, Zhao H. Statistical methods for assessing the effects of de novo variants on birth defects. Human Genomics 2024, 18: 25. PMID: 38486307, PMCID: PMC10938830, DOI: 10.1186/s40246-024-00590-z.Peer-Reviewed Original ResearchConceptsDe novo variantsAnalyzed de novo variantsDevelopment of next-generation sequencing technologiesNext-generation sequencing technologiesSequencing technologiesImprove statistical powerGenetic heterogeneitySequenced samplesStatistical powerBirth defectsDiseased individualsLow occurrenceCongenital heart diseaseVariantsGenesDeleterious effectsSequenceGeneral workflowStatistical methods
2023
Association of Maternal Age and Blood Markers for Metabolic Disease in Newborns
Xie Y, Peng G, Zhao H, Scharfe C. Association of Maternal Age and Blood Markers for Metabolic Disease in Newborns. Metabolites 2023, 14: 5. PMID: 38276295, PMCID: PMC10821442, DOI: 10.3390/metabo14010005.Peer-Reviewed Original ResearchMaternal ageAdvanced maternal ageBlood metabolic markersMaternal age groupsInborn metabolic disordersNeonatal outcomesSingleton infantsGestational ageClinical variablesMarker levelsBirth weightBlood levelsBlood markersRisk factorsAge-related differencesInfant sexMetabolic disordersMetabolic markersPotential confoundingMetabolic diseasesScreening markerAge groupsBlood collectionScreening panelHigh false positive rateStatistical assessment of biomarker replicability using MAJAR method
Xie Y, Zhai S, Jiang W, Zhao H, Mehrotra D, Shen J. Statistical assessment of biomarker replicability using MAJAR method. Statistical Methods In Medical Research 2023, 32: 1961-1972. PMID: 37519295, DOI: 10.1177/09622802231188519.Peer-Reviewed Original ResearchConceptsBayesian false discovery rateDifferent data generation processesNovel statistical frameworkExtensive simulation studyExpectation-maximization algorithmStatistical frameworkComputational efficiencyGWAS summary statistics dataSimulation studyData generation processStatistical assessmentSimulation resultsStatistical powerFalse discovery rateResponse predictionSummary statistics dataDiscovery rateSample sizeLimited powerOutliersAlgorithmGeneration processRobustnessPowerSmall sample sizeWhole-Exome Sequencing Analyses Support a Role of Vitamin D Metabolism in Ischemic Stroke
Xie Y, Acosta J, Ye Y, Demarais Z, Conlon C, Chen M, Zhao H, Falcone G. Whole-Exome Sequencing Analyses Support a Role of Vitamin D Metabolism in Ischemic Stroke. Stroke 2023, 54: 800-809. PMID: 36762557, PMCID: PMC10467223, DOI: 10.1161/strokeaha.122.040883.Peer-Reviewed Original ResearchConceptsGene-based testingRare genetic variationGene-based analysisGenetic variationAssociation studiesGenome-wide association studiesSingle-variant association analysisWide significance levelSusceptibility risk lociWide association studyDeleterious missense variantsMissense rare variantsBonferroni-corrected thresholdWhole-exome sequencing dataRare variantsSingle variant analysisHeritable traitRisk lociExome-wide studySequencing dataExome sequencing analysisAssociation analysisSequencing analysisMissense variantsTraits
2022
Network assisted analysis of de novo variants using protein-protein interaction information identified 46 candidate genes for congenital heart disease
Xie Y, Jiang W, Dong W, Li H, Jin SC, Brueckner M, Zhao H. Network assisted analysis of de novo variants using protein-protein interaction information identified 46 candidate genes for congenital heart disease. PLOS Genetics 2022, 18: e1010252. PMID: 35671298, PMCID: PMC9205499, DOI: 10.1371/journal.pgen.1010252.Peer-Reviewed Original Research
2021
M-DATA: A statistical approach to jointly analyzing de novo mutations for multiple traits
Xie Y, Li M, Dong W, Jiang W, Zhao H. M-DATA: A statistical approach to jointly analyzing de novo mutations for multiple traits. PLOS Genetics 2021, 17: e1009849. PMID: 34735430, PMCID: PMC8568192, DOI: 10.1371/journal.pgen.1009849.Peer-Reviewed Original ResearchA novel transcriptional risk score for risk prediction of complex human diseases
Shan N, Xie Y, Song S, Jiang W, Wang Z, Hou L. A novel transcriptional risk score for risk prediction of complex human diseases. Genetic Epidemiology 2021, 45: 811-820. PMID: 34245595, PMCID: PMC8604733, DOI: 10.1002/gepi.22424.Peer-Reviewed Original ResearchConceptsTranscriptional risk scoreComplex human diseasesHuman diseasesPolygenetic risk scoresComplex traitsFunctional annotationProteomic dataRNA expression levelsGene expressionEffect size distributionMessenger RNA expression levelsMultiomics datasetsMultiple tissuesLinkage disequilibriumExpression levelsTraitsMultiple diseasesAnnoPredLDpredGreater prediction powerReference datasetPhenotypeAnnotationLarge effectDisequilibriumTranscriptome wide association studies: general framework and methods
Xie Y, Shan N, Zhao H, Hou L. Transcriptome wide association studies: general framework and methods. Quantitative Biology 2021, 9: 141-150. DOI: 10.15302/j-qb-020-0228.Peer-Reviewed Original Research