bgsmtr: Bayesian Group Sparse Multi-Task Regression

Fits a Bayesian group-sparse multi-task regression model using Gibbs sampling. The hierarchical prior encourages shrinkage of the estimated regression coefficients at both the gene and SNP level. The model has been extended to a spatial model that allows for two type correlation in neuroimaging genetics data and been applied successfully to imaging phenotypes of dimension up to 100; it can be used more generally for multivariate (non-imaging) phenotypes.

Version: 0.2
Depends: R (≥ 3.3.1), Matrix (≥ 1.2.6), mvtnorm (≥ 1.0.5), matrixcalc (≥ 1.0.3), miscTools (≥ 0.6.22)
Imports: coda (≥ 0.18.1), EDISON (≥ 1.1.1), statmod (≥ 1.4.26), methods (≥ 3.3.3), sparseMVN (≥ 0.2.0), inline (≥ 0.3.15), LaplacesDemon (≥ 16.1.0), TargetScore (≥ 1.12.0), mnormt (≥ 1.5.4), Rcpp (≥ 0.12.14)
Published: 2018-08-26
Author: Yin Song, Shufei Ge, Liangliang Wang, Farouk S. Nathoo, Keelin Greenlaw, Mary Lesperance
Maintainer: Yin Song <yinsong at uvic.ca>
License: GPL-2
NeedsCompilation: no
CRAN checks: bgsmtr results

Downloads:

Reference manual: bgsmtr.pdf
Package source: bgsmtr_0.2.tar.gz
Windows binaries: r-devel: bgsmtr_0.2.zip, r-release: bgsmtr_0.2.zip, r-oldrel: bgsmtr_0.2.zip
OS X binaries: r-release: bgsmtr_0.1.tgz, r-oldrel: bgsmtr_0.1.tgz
Old sources: bgsmtr archive

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