ARTIVA: Infer a time-varying DBN network from time series data
This package generates Reversible Jump MCMC (RJ-MCMC)
sampling for approximating the posterior distribution of a time
varying regulatory network, under the Auto Regressive TIme
VArying (ARTIVA) model (for a detailed description of the
algorithm, see Lebre et al. BMC Systems Biology, 2010).
Starting from time-course gene expression measurements for a
gene of interest (referred to as "target gene") and a set of
genes (referred to as "parent genes") which may explain the
expression of the target gene, the ARTIVA procedure identifies
temporal segments for which a set of interactions occur between
the "parent genes" and the "target gene". The time points that
delimit the different temporal segments are referred to as
changepoints (CP).
| Version: |
1.2.1 |
| Depends: |
MASS, igraph0, gplots |
| Published: |
2012-12-13 |
| Author: |
S. Lebre and G. Lelandais. |
| Maintainer: |
S. Lebre <sophie.lebre at lsiit-cnrs.unistra.fr> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| CRAN checks: |
ARTIVA results |
Downloads: