
Network Analysis and Causal Learning with Structural Equation Modeling
SEMgraph Estimate networks and causal relations in complex systems through Structural Equation Modeling (SEM). SEMgraph comes with the following functionalities:
or the corresponding SEM in lavaan syntax. Model management functions include graph-to-SEM conversion, automated covariance matrix regularization, graph conversion to DAG, and tree (arborescence) from correlation matrices.
parallelization settings for fast fitting in case of very large models.
structure learning and bow-free interaction search and latent variable confounding adjustment.
together with graph plotting utilities, tracing model architecture modifications and perturbation (i.e., activation or repression) routes.
The latest stable version can be installed from CRAN:
install.packages("SEMgraph")
The latest development version can be installed from GitHub:
# install.packages("devtools")
devtools::install_github("fernandoPalluzzi/SEMgraph")
Do not forget to install the SEMdata package too! It contains useful high-throughput sequencing data, reference networks, and pathways for SEMgraph training:
devtools::install_github("fernandoPalluzzi/SEMdata")
install.packages('SEMgraph')