Abstract
Summary Finding meaningful gene-gene associations and the main Transcription Factors (TFs) in co-expression networks is one of the most important challenges in gene expression data mining. CeTF is an R package that integrates the Partial Correlation with Information Theory (PCIT) and Regulatory Impact Factors (RIF) algorithms applied to gene expression data from microarray, RNA-seq, or single-cell RNA-seq platforms. This approach allows identifying the transcription factors most likely to regulate a given network in different biological systems — for example, regulation of gene pathways in tumor stromal cells and tumor cells of the same tumor. This pipeline can be easily integrated into the high-throughput analysis.
Availability CeTF is available as R package in Bioconductor (https://bioconductor.org/packages/CeTF), GitHub (https://github.com/cbiagii/CeTF) and as docker image (https://hub.docker.com/r/biagii/cetf). More information on how to use the package can be found in the Supplemental File 1.