Visualitza per autoria "Schunk, Daniel"

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  • Assessing statistical significance in multivariable genome wide association analysis
    Buzdugan, Laura; Kalisch, Markus; Navarro i Cuartiellas, Arcadi, 1969-; Schunk, Daniel; Fehr, Ernst; Bühlmann, Peter (Oxford University Press, 2016)
    Motivation: Although Genome Wide Association Studies (GWAS) genotype a very large number of single nucleotide polymorphisms (SNPs), the data are often analyzed one SNP at a time. The low predictive power of single SNPs, ...
  • Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies
    Mieth, Bettina; Kloft, Marius; Rodríguez, Juan Antonio; Sonnenburg, Sören; Vobruba, Robin; Morcillo Suárez, Carlos, 1969-; Farré, Xavier; Marigorta, Urko M.; Fehr, Ernst; Dickhaus, Thorsten; Blanchard, Gilles; Schunk, Daniel; Navarro i Cuartiellas, Arcadi, 1969-; Müller, Klaus-Robert (Nature Publishing Group, 2016)
    The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under ...
  • How to analyze many contingency tables simultaneously in genetic association studies
    Dickhaus, Thorsten; Straßburger, Klaus; Schunk, Daniel; Morcillo Suárez, Carlos, 1969-; Illig, Thomas; Navarro i Cuartiellas, Arcadi, 1969- (De Gruyter, 2012)
    We study exact tests for (2 x 2) and (2 x 3) contingency tables, in particular exact chi-squared tests and exact tests of Fisher type. In practice, these tests are typically carried out without randomization, leading to ...

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