Ning Sun, PhD
Senior Research Scientist in BiostatisticsCards
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Senior Research Scientist in Biostatistics
Biography
Dr. Sun is a Research Scientist in the Department of Biostatistics. She received her B.S. in Civil and Environmental Engineering from Tsinghua University in 1991 and Ph.D. in Environmental Engineering from the University of California at Los Angeles in 1998. Prior to her position at Yale School of Public Health, she was a Postdoctoral Associate and Associate Research Scientist in Chemical Engineering at Yale between 1998 and 2000. Dr. Sun has extensive experiences in environmental engineering focusing on modeling contaminant transport in heterogeneous porous media, and she developed a mathematical and computational approach for colloid surface interactions in Chemical Engineering. As a bioinformatician and biostatistician, Dr. Sun is experienced in statistical methods for transcriptome analysis using both gene expression microarray data and next generation sequencing data, regulatory network modeling, data integration methods, functional genomics, and genome wide association studies. Dr. Sun has developed a number of novel statistical methods for more efficient data integration for the purpose of inferring gene expression networks and disease gene identifications.
Appointments
Biostatistics
Senior Research ScientistPrimary
Other Departments & Organizations
Education & Training
- PhD
- University of California at Los Angeles (1998)
- MS
- University of California at Los Angeles (1994)
- BS
- Tsinghua University (1991)
Research
Overview
Medical Subject Headings (MeSH)
Research at a Glance
Yale Co-Authors
Publications Timeline
Research Interests
Hongyu Zhao, PhD
Mihaela Aslan, PhD
Joel Gelernter, MD
Nallakkandi Rajeevan, PhD
Daniel F. Levey, PhD
Amy Justice, MD, PhD
Publications
2020
Genome-wide association study of smoking trajectory and meta-analysis of smoking status in 842,000 individuals
Xu K, Li B, McGinnis KA, Vickers-Smith R, Dao C, Sun N, Kember RL, Zhou H, Becker WC, Gelernter J, Kranzler HR, Zhao H, Justice AC. Genome-wide association study of smoking trajectory and meta-analysis of smoking status in 842,000 individuals. Nature Communications 2020, 11: 5302. PMID: 33082346, PMCID: PMC7598939, DOI: 10.1038/s41467-020-18489-3.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsGenome-wide association studiesLarge genome-wide association studiesMillion Veteran ProgramAssociation studiesExpression quantitative trait lociQuantitative trait lociChromatin interactionsComplex traitsFunctional annotationTrait lociSequencing ConsortiumDozen genesSignificant lociSmoking phenotypesLociMultiple populationsNew insightsPhenotypeVeteran ProgramGenetic vulnerabilityGenesTraitsAnnotationEuropean AmericansConsortiumStatistical Methods in Genome-Wide Association Studies
Sun N, Zhao H. Statistical Methods in Genome-Wide Association Studies. Annual Review Of Biomedical Data Science 2020, 3: 1-24. DOI: 10.1146/annurev-biodatasci-030320-041026.Peer-Reviewed Original ResearchCitationsConceptsGenome-wide association studiesAssociation studiesTraits of interestGenetic architectureIdentification of variantsGWAS dataStatistical methodologyStatistical challengesGenetic risk prediction modelsGenetic markersStatistical methodsHuman diseasesPhenotype informationGenetic variantsTraitsGenotype informationScientific goalsRecent progressGenesVariantsTens of thousandsHundreds of thousandsPrediction modelPathwayThousandsGenotyping Array Design and Data Quality Control in the Million Veteran Program
Hunter-Zinck H, Shi Y, Li M, Gorman BR, Ji SG, Sun N, Webster T, Liem A, Hsieh P, Devineni P, Karnam P, Gong X, Radhakrishnan L, Schmidt J, Assimes TL, Huang J, Pan C, Humphries D, Brophy M, Moser J, Muralidhar S, Huang GD, Przygodzki R, Concato J, Gaziano JM, Gelernter J, O’Donnell C, Hauser ER, Zhao H, O’Leary T, Program V, Tsao PS, Pyarajan S. Genotyping Array Design and Data Quality Control in the Million Veteran Program. American Journal Of Human Genetics 2020, 106: 535-548. PMID: 32243820, PMCID: PMC7118558, DOI: 10.1016/j.ajhg.2020.03.004.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsMillion Veteran ProgramGenome-wide association studiesGenome-wide scanHigh-quality genotypesArray-based genotypingWhole-genome sequencingNon-European individualsAssociation studiesGenetic markersOmics assaysAxiom arrayDownstream analysisVeteran ProgramCommon variantsGenetic associationAfrican American ancestryAmerican ancestryMVP cohortRare variantsSingle assayDiversityFurther data releasesLarge biobanksPromising resourceQuality control
2019
Genome‐wide association study of cognitive performance in U.S. veterans with schizophrenia or bipolar disorder
Harvey PD, Sun N, Bigdeli TB, Fanous AH, Aslan M, Malhotra AK, Lu Q, Hu Y, Li B, Chen Q, Mane S, Miller P, Rajeevan N, Sayward F, Cheung K, Li Y, Greenwood TA, Gur RE, Braff DL, on the Genetics of Schizophrenia C, Brophy M, Pyarajan S, O'Leary TJ, Gleason T, Przygodszki R, Muralidhar S, Gaziano JM, Concato J, Zhao H, Siever LJ. Genome‐wide association study of cognitive performance in U.S. veterans with schizophrenia or bipolar disorder. American Journal Of Medical Genetics Part B Neuropsychiatric Genetics 2019, 183: 181-194. PMID: 31872970, DOI: 10.1002/ajmg.b.32775.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsMeSH KeywordsAdultAgedAllelesBipolar DisorderCognitionCognition DisordersFemaleGenome-Wide Association StudyGenotypeHumansMaleMiddle AgedNeuropsychological TestsOligonucleotide Array Sequence AnalysisPolymorphism, Single NucleotideSchizophreniaUnited StatesUnited States Department of Veterans AffairsVeteransGENOMICS OF SUICIDAL IDEATION AND BEHAVIOR IN VETERANS WITH SEVERE MENTAL ILLNESS
Harvey P, Bigdeli T, Fanous A, Aslan M, Sun N, Zhao H. GENOMICS OF SUICIDAL IDEATION AND BEHAVIOR IN VETERANS WITH SEVERE MENTAL ILLNESS. European Neuropsychopharmacology 2019, 29: s34. DOI: 10.1016/j.euroneuro.2019.07.069.Peer-Reviewed Original ResearchGenome-wide association study of post-traumatic stress disorder reexperiencing symptoms in >165,000 US veterans
Gelernter J, Sun N, Polimanti R, Pietrzak R, Levey DF, Bryois J, Lu Q, Hu Y, Li B, Radhakrishnan K, Aslan M, Cheung KH, Li Y, Rajeevan N, Sayward F, Harrington K, Chen Q, Cho K, Pyarajan S, Sullivan PF, Quaden R, Shi Y, Hunter-Zinck H, Gaziano JM, Concato J, Zhao H, Stein MB. Genome-wide association study of post-traumatic stress disorder reexperiencing symptoms in >165,000 US veterans. Nature Neuroscience 2019, 22: 1394-1401. PMID: 31358989, PMCID: PMC6953633, DOI: 10.1038/s41593-019-0447-7.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsGenome-wide association studiesAssociation studiesHigh linkage disequilibrium regionLinkage disequilibrium regionWide association studyDisequilibrium regionBioinformatics analysisTranscriptomic profilesMillion Veteran ProgramChromosome 17Genetic risk factorsNew insightsUK Biobank dataReexperiencing of traumaStriatal medium spiny neuronsVeteran ProgramSignificant regionsCAMKVEuropean AmericansBiobank dataMedium spiny neuronsTCF4BiologyKANSL1African American cohortS93. GENOMICS OF SUICIDAL IDEATION AND BEHAVIOR IN VETERANS WITH SCHIZOPHRENIA AND BIPOLAR ILLNESS
Harvey P, Aslan M, Sun N, Zhao H, Concato J. S93. GENOMICS OF SUICIDAL IDEATION AND BEHAVIOR IN VETERANS WITH SCHIZOPHRENIA AND BIPOLAR ILLNESS. Schizophrenia Bulletin 2019, 45: s342-s342. PMCID: PMC6455790, DOI: 10.1093/schbul/sbz020.638.Peer-Reviewed Original ResearchGenome-wide Association Study of Maximum Habitual Alcohol Intake in >140,000 U.S. European and African American Veterans Yields Novel Risk Loci
Gelernter J, Sun N, Polimanti R, Pietrzak RH, Levey DF, Lu Q, Hu Y, Li B, Radhakrishnan K, Aslan M, Cheung KH, Li Y, Rajeevan N, Sayward F, Harrington K, Chen Q, Cho K, Honerlaw J, Pyarajan S, Lencz T, Quaden R, Shi Y, Hunter-Zinck H, Gaziano JM, Kranzler HR, Concato J, Zhao H, Stein MB, Program D, Program M. Genome-wide Association Study of Maximum Habitual Alcohol Intake in >140,000 U.S. European and African American Veterans Yields Novel Risk Loci. Biological Psychiatry 2019, 86: 365-376. PMID: 31151762, PMCID: PMC6919570, DOI: 10.1016/j.biopsych.2019.03.984.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsAdditional genome-wide significant lociRisk lociWide association study (GWAS) analysisAssociation studiesGenome-wide significant lociGenome-wide association studiesGenetic correlationsWide association studyNovel risk lociAlcohol-related traitsStrong statistical supportSmoking-related traitsAdditional genomesSignificant lociPancreatic delta cellsChromosome 4Chromosome 11Protein productsChromosome 8Quantitative phenotypesMillion Veteran ProgramVeterans Affairs Million Veteran ProgramLociCell typesChromosome 17STUDIES ON ALCOHOL DEPENDENCE GENETICS FROM YALE-PENN AND THE MVP
Gelernter J, Sun N, Polimanti R, Zhou H, Levey D, Harrington K, Gaziano M, Pyarajan S, Aslan M, Sayward F, Li B, Farrer L, Zhao H, Concato J, Stein M. STUDIES ON ALCOHOL DEPENDENCE GENETICS FROM YALE-PENN AND THE MVP. European Neuropsychopharmacology 2019, 29: s1035-s1036. DOI: 10.1016/j.euroneuro.2018.07.032.Peer-Reviewed Original ResearchRESULTS FROM THE USVA MVP PTSD COOPERATIVE STUDY GWAS: PCL TRAITS
Gelernter J, Sun N, Polimanti R, Zhou H, Pietrzak R, Levey D, Harrington K, Gaziano M, Pyarajan S, Radhakrishnan K, Hu Y, Li B, Zhao H, Concato J, Stein M. RESULTS FROM THE USVA MVP PTSD COOPERATIVE STUDY GWAS: PCL TRAITS. European Neuropsychopharmacology 2019, 29: s1055-s1056. DOI: 10.1016/j.euroneuro.2018.07.071.Peer-Reviewed Original Research
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