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Andrew Dahl

TitleAssistant Professor
InstitutionUniversity of Chicago
DepartmentMedicine-Genetic Medicine
AddressChicago IL 60637
Email
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    Collapse Overview 
    Collapse overview
    Our group focuses on computational approaches to discover and characterize novel subtypes of complex diseases. Our long-term goal is to advance precision treatment by identifying disease subtypes with distinct biological etiology, clinical presentation, and/or treatment responses. Our subtyping methods build on basic tools from statistical genetics, functional genomics, and linear algebra. We also develop methods for gene-environment interaction, gene-gene interaction, pleiotropy, and confounder correction, which can be invaluable for characterizing subtypes. We apply these methods to disease areas with dramatic and under-characterized heterogeneity. Currently we focus on asthma, psychiatry, and single cell genomics.


    Collapse Biography 
    Collapse education and training
    OxfordPhD10/2016Gen Med and Stats
    UChicagoMS06/2012Stats
    UChicagoHon BS06/2012Math
    UChicagoBA06/2012Econ
    Collapse awards and honors
    2012 - 2016Wellcome Trust Studentship, Oxford
    2012Phi Beta Kappa, UChicago

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    Collapse Bibliographic 
    Collapse selected publications
    Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
    List All   |   Timeline
    1. Dahl A, Zaitlen N. Genetic Influences on Disease Subtypes. Annu Rev Genomics Hum Genet. 2020 08 31; 21:413-435. PMID: 32873077.
      View in: PubMed
    2. Liu X, Mefford JA, Dahl A, He Y, Subramaniam M, Battle A, Price AL, Zaitlen N. GBAT: a gene-based association test for robust detection of trans-gene regulation. Genome Biol. 2020 08 24; 21(1):211. PMID: 32831138.
      View in: PubMed
    3. Keys KL, Mak ACY, White MJ, Eckalbar WL, Dahl AW, Mefford J, Mikhaylova AV, Contreras MG, Elhawary JR, Eng C, Hu D, Huntsman S, Oh SS, Salazar S, Lenoir MA, Ye JC, Thornton TA, Zaitlen N, Burchard EG, Gignoux CR. On the cross-population generalizability of gene expression prediction models. PLoS Genet. 2020 08; 16(8):e1008927. PMID: 32797036.
      View in: PubMed
    4. Steinsaltz D, Dahl A, Wachter KW. On Negative Heritability and Negative Estimates of Heritability. Genetics. 2020 06; 215(2):343-357. PMID: 32291292.
      View in: PubMed
    5. Dahl A, Nguyen K, Cai N, Gandal MJ, Flint J, Zaitlen N. A Robust Method Uncovers Significant Context-Specific Heritability in Diverse Complex Traits. Am J Hum Genet. 2020 01 02; 106(1):71-91. PMID: 31901249.
      View in: PubMed
    6. Hernandez RD, Uricchio LH, Hartman K, Ye C, Dahl A, Zaitlen N. Ultrarare variants drive substantial cis heritability of human gene expression. Nat Genet. 2019 09; 51(9):1349-1355. PMID: 31477931.
      View in: PubMed
    7. Dahl A, Cai N, Ko A, Laakso M, Pajukanta P, Flint J, Zaitlen N. Reverse GWAS: Using genetics to identify and model phenotypic subtypes. PLoS Genet. 2019 04; 15(4):e1008009. PMID: 30951530.
      View in: PubMed
    8. Dahl A, Guillemot V, Mefford J, Aschard H, Zaitlen N. Adjusting for Principal Components of Molecular Phenotypes Induces Replicating False Positives. Genetics. 2019 04; 211(4):1179-1189. PMID: 30692194.
      View in: PubMed
    9. Steinsaltz D, Dahl A, Wachter KW. Statistical properties of simple random-effects models for genetic heritability. Electron J Stat. 2018; 12(1):321-356. PMID: 30057658.
      View in: PubMed
    10. Dahl A, Iotchkova V, Baud A, Johansson Å, Gyllensten U, Soranzo N, Mott R, Kranis A, Marchini J. A multiple-phenotype imputation method for genetic studies. Nat Genet. 2016 Apr; 48(4):466-72. PMID: 26901065.
      View in: PubMed
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