SEMgsa: topology-based pathway enrichment analysis with structural equation models.

Published in: BMC bioinformatics (2022)

SEMgsa is a novel yet powerful method for identifying enrichment with regard to gene expression data. It takes into account topological information and exploits pathway perturbation statistics to reveal biological information. SEMgsa is implemented in the R package SEMgraph, easily available at https://CRAN.R-project.org/package=SEMgraph .

Keyphrases

gene expression
health information
dna methylation
quality improvement
genome wide
electronic health record
big data
healthcare
single cell
data analysis
artificial intelligence
deep learning