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

ABSTRACT:

Background

Pathway enrichment analysis is extensively used in high-throughput experimental studies to gain insight into the functional roles of pre-defined subsets of genes, proteins and metabolites. Methods that leverages information on the topology of the underlying pathways outperform simpler methods that only consider pathway membership, leading to improved performance. Among all the proposed software tools, there's the need to combine high statistical power together with a user-friendly framework, making it difficult to choose the best method for a particular experimental environment.

Results

We propose SEMgsa, a topology-based algorithm developed into the framework of structural equation models. SEMgsa combine the SEM p values regarding node-specific group effect estim

SUBMITTER: Grassi M 

PROVIDER: S-EPMC9385099 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature