2019
Improving Genetic Association Analysis through Integration of Functional Annotations of the Human Genome
Lu Q, Zhao H. Improving Genetic Association Analysis through Integration of Functional Annotations of the Human Genome. 2019, 679-30. DOI: 10.1002/9781119487845.ch24.Peer-Reviewed Original ResearchGenome-wide association studiesFunctional annotationHuman genomeAssociation analysisAnnotation dataFunctional annotation dataPost-GWAS analysisSummary association statisticsGenetic association analysisGWAS findingsGWAS dataIntegrative analysisAssociation studiesComplex diseasesAssociation statisticsGenetic associationGenomeComputational methodsAnnotationTraitsDirect applicationStatistical powerMost diseasesInterpretable metricsTens of thousands
2017
Systematic tissue-specific functional annotation of the human genome highlights immune-related DNA elements for late-onset Alzheimer’s disease
Lu Q, Powles RL, Abdallah S, Ou D, Wang Q, Hu Y, Lu Y, Liu W, Li B, Mukherjee S, Crane PK, Zhao H. Systematic tissue-specific functional annotation of the human genome highlights immune-related DNA elements for late-onset Alzheimer’s disease. PLOS Genetics 2017, 13: e1006933. PMID: 28742084, PMCID: PMC5546707, DOI: 10.1371/journal.pgen.1006933.Peer-Reviewed Original ResearchConceptsTissue typesNon-coding elementsNon-coding genomeComplex human diseasesLate-onset Alzheimer's diseaseIndividual cell typesRelevant tissue typesGWAS traitsTranscriptomic annotationGenome annotationFunctional annotationDNA elementsHeritability enrichmentHuman genomeLarge international consortiaVariety of cellsGenomeHuman diseasesAnnotation dataCell typesGenetic variantsOrgan system categoriesComplex diseasesSimilar localizationAnnotation
2015
A Statistical Framework to Predict Functional Non-Coding Regions in the Human Genome Through Integrated Analysis of Annotation Data
Lu Q, Hu Y, Sun J, Cheng Y, Cheung KH, Zhao H. A Statistical Framework to Predict Functional Non-Coding Regions in the Human Genome Through Integrated Analysis of Annotation Data. Scientific Reports 2015, 5: 10576. PMID: 26015273, PMCID: PMC4444969, DOI: 10.1038/srep10576.Peer-Reviewed Original ResearchConceptsHuman genomeFunctional regionsStatistical frameworkAnnotation dataFunctional annotation dataWhole-genome annotationNon-coding regionsGenomic conservationHigh-throughput experimentsENCODE projectExperimental annotationsGenomeUnsupervised statistical learningFunctional potentialHuman geneticsStatistical learningComputational predictionsIntegrated analysisAnnotationAnnotation methodDiverse typesPowerful toolGeneticsMajor goalWeb server
2014
Statistical Methods for the Analysis of Next Generation Sequencing Data from Paired Tumor-Normal Samples
Chen M, Hou L, Zhao H. Statistical Methods for the Analysis of Next Generation Sequencing Data from Paired Tumor-Normal Samples. Frontiers In Probability And The Statistical Sciences 2014, 379-404. DOI: 10.1007/978-3-319-07212-8_19.Peer-Reviewed Original ResearchStatistical methodsSingle nucleotide alterationsSequencing dataNext-generation sequencing technologiesGeneration sequencing technologyNext-generation sequencing dataGeneration sequencing dataGenomic eraNormal sequencing dataTumor-normal samplesCancer genomesSequencing technologiesSomatic variationNucleotide alterationsNumber alterationsUnprecedented resolutionDNA levelsGenomeAlterations
2003
Chromosome Maps
Speed T, Zhao H. Chromosome Maps. 2003 DOI: 10.1002/0470022620.bbc01.Peer-Reviewed Original Research
1997
Strategies to Identify Genes for Complex Diseases
Zhang H, Zhao H, Merikangas K. Strategies to Identify Genes for Complex Diseases. Annals Of Medicine 1997, 29: 493-498. PMID: 9562515, DOI: 10.3109/07853899709007473.Peer-Reviewed Original ResearchConceptsComplex diseasesNumerous human diseasesDisease-susceptible genesComplex human disordersHuman genomeGenetic basisHuman disordersHuman diseasesMolecular biologyGenesGenetic epidemiological studiesGenetic factorsComplex patternsDisease pathophysiologyGenomeBiologyTraitsInheritanceMultiple sclerosisBreast cancerEpidemiological studies