iCARH: Integrative Conditional Autoregressive Horseshoe Model
Implements the integrative conditional autoregressive horseshoe model
discussed in Jendoubi, T., Ebbels, T.M. Integrative analysis of time course metabolic data and biomarker discovery.
BMC Bioinformatics 21, 11 (2020) <doi:10.1186/s12859-019-3333-0>.
The model consists in three levels: Metabolic pathways level modeling interdependencies between
variables via a conditional auto-regressive (CAR) component, integrative analysis level to identify
potential associations between heterogeneous omic variables via a Horseshoe prior and experimental
design level to capture experimental design conditions through a mixed-effects model.
The package also provides functions to simulate data from the model, construct pathway matrices,
post process and plot model parameters.
Version: |
2.0.2.1 |
Depends: |
rstan, MASS, stats, ggplot2, glue |
Imports: |
RCurl, KEGGgraph, igraph, reshape2, mc2d, abind, Matrix |
Suggests: |
knitr, rmarkdown |
Published: |
2020-08-27 |
DOI: |
10.32614/CRAN.package.iCARH |
Author: |
Takoua Jendoubi [aut, cre],
Timothy M.D. Ebbels [aut] |
Maintainer: |
Takoua Jendoubi <t.jendoubi14 at imperial.ac.uk> |
License: |
GPL (≥ 3) |
NeedsCompilation: |
no |
In views: |
Omics |
CRAN checks: |
iCARH results |
Documentation:
Downloads:
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