Noah Zaitlen

Summary

Affiliation: Harvard University
Country: USA

Publications

  1. pmc Informed conditioning on clinical covariates increases power in case-control association studies
    Noah Zaitlen
    Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
    PLoS Genet 8:e1003032. 2012
  2. pmc Analysis of case-control association studies with known risk variants
    Noah Zaitlen
    Department of Epidemiology, Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
    Bioinformatics 28:1729-37. 2012
  3. pmc Heritability in the genome-wide association era
    Noah Zaitlen
    Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Hum Genet 131:1655-64. 2012
  4. pmc A nonparametric test to detect quantitative trait loci where the phenotypic distribution differs by genotypes
    Hugues Aschard
    Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Genet Epidemiol 37:323-33. 2013
  5. pmc Enhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium
    Bogdan Pasaniuc
    Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
    PLoS Genet 7:e1001371. 2011
  6. doi request reprint Variation in predictive ability of common genetic variants by established strata: the example of breast cancer and age
    Hugues Aschard
    From the aProgram in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, MA bDepartment of Medicine, University of California San Francisco, San Francisco, CA and cDepartment of Biostatistics, Harvard School of Public Health, Boston, MA
    Epidemiology 26:51-8. 2015
  7. doi request reprint Fast and accurate imputation of summary statistics enhances evidence of functional enrichment
    Bogdan Pasaniuc
    Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, 90024, Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, 90024, Department of Medicine, Lung Biology Center, University of California San Francisco, San Francisco, 94143, Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, 02115, Departments of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, MA, 02115, Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, 02142, Department of Genetics Harvard Medical School, Boston, MA, 02115 and Division of Population Health Sciences and Education, St George s, University of London, UK Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, 90024, Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, 90024, Department of Medicine, Lung Biology Center, University of California San Francisco, San Francisco, 94143, Program in Genetic Epidemiology and Statistical Genetics, France
    Bioinformatics 30:2906-14. 2014
  8. pmc Combining effects from rare and common genetic variants in an exome-wide association study of sequence data
    Hugues Aschard
    1Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
    BMC Proc 5:S44. 2011
  9. pmc Extremely low-coverage sequencing and imputation increases power for genome-wide association studies
    Bogdan Pasaniuc
    Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
    Nat Genet 44:631-5. 2012

Detail Information

Publications9

  1. pmc Informed conditioning on clinical covariates increases power in case-control association studies
    Noah Zaitlen
    Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
    PLoS Genet 8:e1003032. 2012
    ..This suggests that applying our method to existing and future association studies of these diseases may identify novel disease loci...
  2. pmc Analysis of case-control association studies with known risk variants
    Noah Zaitlen
    Department of Epidemiology, Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
    Bioinformatics 28:1729-37. 2012
    ..Roughly, this method estimates model parameters for each known variant while accounting for the published disease prevalence from the epidemiological literature...
  3. pmc Heritability in the genome-wide association era
    Noah Zaitlen
    Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Hum Genet 131:1655-64. 2012
    ..We discuss them in the context of classical heritability methods, the missing heritability problem, and describe their implications for understanding the genetic architecture of complex phenotypes...
  4. pmc A nonparametric test to detect quantitative trait loci where the phenotypic distribution differs by genotypes
    Hugues Aschard
    Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
    Genet Epidemiol 37:323-33. 2013
    ..We demonstrate the potential utility of our method on real data by analyzing mammographic density genome-wide data from the Nurses' Health Study...
  5. pmc Enhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium
    Bogdan Pasaniuc
    Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
    PLoS Genet 7:e1001371. 2011
    ..Our methods and our publicly available software are broadly applicable to GWAS in admixed populations...
  6. doi request reprint Variation in predictive ability of common genetic variants by established strata: the example of breast cancer and age
    Hugues Aschard
    From the aProgram in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, MA bDepartment of Medicine, University of California San Francisco, San Francisco, CA and cDepartment of Biostatistics, Harvard School of Public Health, Boston, MA
    Epidemiology 26:51-8. 2015
    ..However, the clinical utility of common breast cancer risk markers may nonetheless differ across strata defined by known risk factors, such as age...
  7. doi request reprint Fast and accurate imputation of summary statistics enhances evidence of functional enrichment
    Bogdan Pasaniuc
    Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, 90024, Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, 90024, Department of Medicine, Lung Biology Center, University of California San Francisco, San Francisco, 94143, Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, 02115, Departments of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, MA, 02115, Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, 02142, Department of Genetics Harvard Medical School, Boston, MA, 02115 and Division of Population Health Sciences and Education, St George s, University of London, UK Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, 90024, Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, 90024, Department of Medicine, Lung Biology Center, University of California San Francisco, San Francisco, 94143, Program in Genetic Epidemiology and Statistical Genetics, France
    Bioinformatics 30:2906-14. 2014
    ..Here, we develop a new method for Gaussian imputation from summary association statistics, a type of data that is becoming widely available...
  8. pmc Combining effects from rare and common genetic variants in an exome-wide association study of sequence data
    Hugues Aschard
    1Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
    BMC Proc 5:S44. 2011
    ....
  9. pmc Extremely low-coverage sequencing and imputation increases power for genome-wide association studies
    Bogdan Pasaniuc
    Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
    Nat Genet 44:631-5. 2012
    ....