README.md

In fernandoPalluzzi/SEMdata: Datasets for SEM-based network analysis using the SEMgraph R package

SEMdata

High-throughput sequencing data and reference networks to get trained with the R package SEMgraph.

Overview

SEMgraph is an R package for network analysis and causal inference and learning through Structural Equation Modeling (SEM). It comes with the following functionalities:

• Interchangeable model representation as either an igraph object or the corresponding SEM in lavaan syntax. Model management functions include graph-to-SEM conversion, automated covariance matrix regularization, graph conversion to DAG, and graph creation from correlation matrices.

• Heuristic filtering, node and edge weighting, resampling and parallelization settings for fast fitting in case of very large models.

• Automated data-driven model building and improvement, through causal structure learning, bow-free interaction search, and latent variable confounding adjustment.

• Perturbed paths finding, community searching and sample scoring, together with graph plotting utilities, tracing model architecture modifications and perturbation (i.e., activation or repression) routes.

Installation

The development version of SEMdata can be installed in R with the following line (it requires SEMgraph first):

{r, echo = FALSE} devtools::install_github("fernandoPalluzzi/SEMgraph") devtools::install_github("fernandoPalluzzi/SEMdata")

fernandoPalluzzi/SEMdata documentation built on June 27, 2022, 7:04 a.m.