New Results
Fast and Accurate Bayesian Polygenic Risk Modeling with Variational Inference
View ORCID ProfileShadi Zabad, Simon Gravel, Yue Li
doi: https://doi.org/10.1101/2022.05.10.491396
Shadi Zabad
1School of Computer Science, McGill University
Simon Gravel
2Department of Human Genetics, McGill University
Yue Li
1School of Computer Science, McGill University
Article usage
Posted May 11, 2022.
Fast and Accurate Bayesian Polygenic Risk Modeling with Variational Inference
Shadi Zabad, Simon Gravel, Yue Li
bioRxiv 2022.05.10.491396; doi: https://doi.org/10.1101/2022.05.10.491396
Subject Area
Subject Areas
- Biochemistry (11752)
- Bioengineering (8752)
- Bioinformatics (29200)
- Biophysics (14974)
- Cancer Biology (12096)
- Cell Biology (17411)
- Clinical Trials (138)
- Developmental Biology (9421)
- Ecology (14182)
- Epidemiology (2067)
- Evolutionary Biology (18308)
- Genetics (12245)
- Genomics (16803)
- Immunology (11869)
- Microbiology (28097)
- Molecular Biology (11594)
- Neuroscience (60969)
- Paleontology (451)
- Pathology (1871)
- Pharmacology and Toxicology (3238)
- Physiology (4959)
- Plant Biology (10427)
- Synthetic Biology (2886)
- Systems Biology (7340)
- Zoology (1651)