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1.
Ogloblinsky, M.C.* et al.: PSAP-Genomic-Regions: A method leveraging population data to prioritize coding and non-coding variants in whole genome sequencing for rare Disease diagnosis. Genet. Epidemiol., DOI: 10.1002/gepi.22593 (2024)
2.
Bocher, O. ; Marenne, G.* ; Genin, E.* & Perdry, H.*: Ravages: An R package for the simulation and analysis of rare variants in multicategory phenotypes. Genet. Epidemiol. 47, 450-460 (2023)
3.
Bauer, A. et al.: Comparison of genetic risk prediction models to improve prediction of coronary heart disease in two large cohorts of the MONICA/KORA study. Genet. Epidemiol. 45, 633-650 (2021)
4.
Sun, R.* et al.: Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer. Genet. Epidemiol. 45, 99-114 (2021)
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Png, G. et al.: Population-wide copy number variation calling using variant call format files from 6,898 individuals. Genet. Epidemiol. 44, 79-89 (2020)
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Müller-Nurasyid, M. et al.: Pharmacogenetic effects in population-based metabolic profiles. Genet. Epidemiol. 42, 719-720 (2018)
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Cuellar-Partida, G.* et al.: Assessing the genetic predisposition of education on myopia: A mendelian randomization study. Genet. Epidemiol. 40, 66-72 (2016)
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Asimit, J.L.* et al.: A Bayesian approach to the overlap analysis of epidemiologically linked traits. Genet. Epidemiol. 39, 624-634 (2015)
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Dankowski, T.* et al.: Successful replication of GWAS hits for multiple sclerosis in 10,000 Germans using the exome array. Genet. Epidemiol. 39, 601-608 (2015)
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Friedrichs, S.* et al.: Kernel-based pathway meta-analysis in ILCCO / TRICL genome-wide association studies. Genet. Epidemiol. 39, 549 (2015)
11.
Ma, C.* ; Boehnke, M.* ; Lee, S.* & GoT2D Consortium (Gieger, C. ; Grallert, H. ; Hrabě de Angelis, M. ; Huth, C. ; Kriebel, J. ; Meisinger, C. ; Meitinger, T. ; Müller-Nurasyid, M. ; Peters, A. ; Ried, J.S. ; Strauch, K. ; Strom, T.M.): Evaluating the calibration and power of three gene-based association tests of rare variants for the X chromosome. Genet. Epidemiol. 39, 499-508 (2015)
12.
Müller-Nurasyid, M. et al.: Genome-wide association analysis with multivariate ECG traits. Genet. Epidemiol. 39, 571 (2015)
13.
Poirier, J.G.* et al.: Informed genome-wide association analysis with family history as a secondary phenotype identifies novel loci of lung cancer. Genet. Epidemiol. 39, 197-206 (2015)
14.
Rosenberger, A.* et al.: Meta-analysis of gene-set analyses based on genome wide association studies, method development and application within ILCCO/TRICL consortia. Genet. Epidemiol. 39, 576 (2015)
15.
Gorski, M.* et al.: Harmonization of study and reference data by PhaseLift: Saving time when imputing study data. Genet. Epidemiol. 38, 381-388 (2014)
16.
Ma, C.* ; Blackwell, T.* ; Boehnke, M.* ; Scott, L.J.* & GoT2D Consortium (Gieger, C. ; Grallert, H. ; Hrabě de Angelis, M. ; Huth, C. ; Kriebel, J. ; Meisinger, C. ; Meitinger, T. ; Müller-Nurasyid, M. ; Peters, A. ; Rathmann, W. ; Ried, J.S. ; Strauch, K. ; Strom, T.M.): Recommended joint and meta-analysis strategies for case-control association testing of single low-count variants. Genet. Epidemiol. 37, 539-550 (2013)
17.
Minelli, C.* et al.: Importance of different types of prior knowledge in selecting genome-wide findings for follow-up. Genet. Epidemiol. 37, 205-213 (2013)
18.
Sohns, M.* et al.: Empirical hierarchical Bayes approach to gene-environment interactions: Development and application to genome-wide association studies of lung cancer in TRICL. Genet. Epidemiol. 37, 551-559 (2013)
19.
Thompson, J.R.* et al.: SNP prioritization using a Bayesian probability of association. Genet. Epidemiol. 37, 214-221 (2013)
20.
Behrens, G.* ; Winkler, T.W.* ; Gorski, M. ; Leitzmann, M.F.* & Heid, I.M.: To stratify or not to stratify: Power considerations for population-based genome-wide association studies of quantitative traits. Genet. Epidemiol. 35, 867-879 (2012)
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