New Results
A Modeling Framework for Exploring Sampling and Observation Process Biases in Genome and Phenome-wide Association Studies using Electronic Health Records
View ORCID ProfileLauren J. Beesley, View ORCID ProfileLars G. Fritsche, Bhramar Mukherjee
doi: https://doi.org/10.1101/499392
Lauren J. Beesley
1University of Michigan, Department of Biostatistics
Lars G. Fritsche
1University of Michigan, Department of Biostatistics
Bhramar Mukherjee
1University of Michigan, Department of Biostatistics
Article usage
Posted May 14, 2019.
A Modeling Framework for Exploring Sampling and Observation Process Biases in Genome and Phenome-wide Association Studies using Electronic Health Records
Lauren J. Beesley, Lars G. Fritsche, Bhramar Mukherjee
bioRxiv 499392; doi: https://doi.org/10.1101/499392
Subject Area
Subject Areas
- Biochemistry (11718)
- Bioengineering (8724)
- Bioinformatics (29132)
- Biophysics (14936)
- Cancer Biology (12051)
- Cell Biology (17360)
- Clinical Trials (138)
- Developmental Biology (9406)
- Ecology (14146)
- Epidemiology (2067)
- Evolutionary Biology (18269)
- Genetics (12223)
- Genomics (16768)
- Immunology (11844)
- Microbiology (28016)
- Molecular Biology (11560)
- Neuroscience (60822)
- Paleontology (450)
- Pathology (1864)
- Pharmacology and Toxicology (3231)
- Physiology (4940)
- Plant Biology (10401)
- Synthetic Biology (2878)
- Systems Biology (7333)
- Zoology (1642)