A global-local approach for detecting hotspots in multiple-response regression
We tackle modelling and inference for variable selection in regression problems with many predictors and many responses. We focus on detecting hotspots, that is, predictors associated with several responses. Such a task is critical in statistical genetics, as hotspot genetic variants shape the archi...
Main Authors: | Ruffieux, H, Davison, AC, Hager, J, Inshaw, J, Fairfax, BP, Richardson, S, Bottolo, L |
---|---|
Format: | Journal article |
Language: | English |
Published: |
Institute of Mathematical Statistics
2020
|
Similar Items
-
The chromosome 6q22.33 region is associated with age at diagnosis of type 1 diabetes and disease risk in those diagnosed under 5 years of age.
by: Inshaw, J, et al.
Published: (2017) -
R2GUESS: A Graphics Processing Unit-Based R Package for Bayesian Variable Selection Regression of Multivariate Responses
by: Benoît Liquet, et al.
Published: (2016-01-01) -
A fine-scale map of recombination rates and hotspots across the human genome.
by: Myers, S, et al.
Published: (2005) -
Global land degradation hotspots based on multiple methods and indicators
by: Kang Jiang, et al.
Published: (2024-01-01) -
BayesSUR: An R Package for High-Dimensional Multivariate Bayesian Variable and Covariance Selection in Linear Regression
by: Zhi Zhao, et al.
Published: (2021-11-01)