2014
GPA: A Statistical Approach to Prioritizing GWAS Results by Integrating Pleiotropy and Annotation
Chung D, Yang C, Li C, Gelernter J, Zhao H. GPA: A Statistical Approach to Prioritizing GWAS Results by Integrating Pleiotropy and Annotation. PLOS Genetics 2014, 10: e1004787. PMID: 25393678, PMCID: PMC4230845, DOI: 10.1371/journal.pgen.1004787.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesFunctional annotationGWAS datasetsAnnotation informationStatistical approachMultiple GWAS datasetsGenome-wide markersPowerful statistical methodsSingle-phenotype analysisCentral nervous system genesRisk variantsNervous system genesGenotype-Tissue Expression (GTEx) databaseComplex diseasesGWAS data setsSignificant pleiotropic effectsCommon risk basisDifferent complex diseasesDNase-seq dataCell linesStatistical inferenceGenetic architectureGWAS hitsGWAS resultsNovel statistical approach
2012
Time course RNA-seq: A potential avenue with somewhat different approach in tandem of differential analysis
Oh S, Zhao H, Noonan J. Time course RNA-seq: A potential avenue with somewhat different approach in tandem of differential analysis. 2012, 1: 580-587. DOI: 10.1109/cisis.2012.204.Peer-Reviewed Original ResearchMonte Carlo simulation studySimulation studyReal data setsStatistical frameworkDifferential expression methodsStatistical approachDependent dataMarkov model approachInherent dependenciesTime seriesModel approachHidden Markov Model ApproachStandard approachTime-series RNA-seq dataData setsIntuitive solutionBiological systemsTrajectory indexTemporal complexityDifferential analysisDifferent approachesApproachConsiderable advantagesSolution
2000
Multipoint Genetic Mapping with Uniparental Disomy Data
Zhao H, Li J, Robinson W. Multipoint Genetic Mapping with Uniparental Disomy Data. American Journal Of Human Genetics 2000, 67: 851-861. PMID: 10958760, PMCID: PMC1287890, DOI: 10.1086/303072.Peer-Reviewed Original Research