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
2022
Mendelian randomization for causal inference accounting for pleiotropy and sample structure using genome-wide summary statistics
Hu X, Zhao J, Lin Z, Wang Y, Peng H, Zhao H, Wan X, Yang C. Mendelian randomization for causal inference accounting for pleiotropy and sample structure using genome-wide summary statistics. Proceedings Of The National Academy Of Sciences Of The United States Of America 2022, 119: e2106858119. PMID: 35787050, PMCID: PMC9282238, DOI: 10.1073/pnas.2106858119.Peer-Reviewed Original Research
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