Finite adaptation and multistep moves in the metropolis-hastings algorithm for variable selection in genome-wide association analysis.
High-dimensional datasets with large amounts of redundant information are nowadays available for hypothesis-free exploration of scientific questions. A particular case is genome-wide association analysis, where variations in the genome are searched for effects on disease or other traits. Bayesian va...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2012-01-01
|
| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC3499564?pdf=render |