bioRxivBioinformaticsPreprint
CeTF: an R package to Coexpression forTranscription Factors using Regulatory ImpactFactors (RIF) and Partial Correlation andInformation (PCIT) analysis
Carlos Alberto Oliveira de BiagiiD, Ricardo Perecin NocitiiD, Breno Osvaldo Funicheli, Patrícia de Cássia RuyiD, João Paulo Bianchi XimeneziD, Wilson A. SilvaiD
Abstract
SummaryFinding 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. AvailabilityCeTF 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.
- assay: bulk RNA-seq
- assay: scRNA-seq
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 4
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