The analysis of modular gene co-expression networks is a well-established method commonly used for discovering the systems-level functionality of genes. In addition, these studies provide a basis for the discovery of clinically relevant molecular pathways underlying different diseases and conditions.
Researchers at the University of São Paulo developed a fast and easy-to-use Bioconductor package named CEMiTool that unifies the discovery and the analysis of co-expression modules. Using the same real datasets, they demonstrate that CEMiTool outperforms existing tools, and provides unique results in a user-friendly html report with high quality graphs. Among its features, our tool evaluates whether modules contain genes that are over-represented by specific pathways or that are altered in a specific sample group, as well as it integrates transcriptomic data with interactome information, identifying the potential hubs on each network. The researchers successfully applied CEMiTool to over 1000 transcriptome datasets, and to a new RNA-seq dataset of patients infected with Leishmania, revealing novel insights of the disease’s physiopathology.
Overview of CEMiTool
a CEMiTool requires a gene expression file to identify the modules and optional files to: (b) visualize the expression profile of individual genes across samples from different groups, which are defined by the user and shown as different colors; (c) perform Gene Set Enrichment Analyses, showing the module activity on each group of samples; (d) run over representation analysis to define module functions; and (e) create gene networks, displaying the top ten most connected genes (hubs)
The CEMiTool R package provides users with an easy-to-use method to automatically implement gene co-expression network analyses, obtain key information about the discovered gene modules using additional downstream analyses and retrieve publication-ready results via a high-quality interactive report.
Availability – The CEMiTool package is available at Bioconductor (DOI: https://doi.org/10.18129/B9.bioc.CEMiTool) and can be downloaded using the command biocLite (“CEMiTool”) (package BiocInstaller v. > = 1.28.0). A Docker image with an environment specifically tailored for CEMiTool analyses is also available at DockerHub (https://hub.docker.com/r/csblusp/cemitool/).