ArticleBMC genomics2021
CeTF: an R/Bioconductor package for transcription factor co-expression networks using regulatory impact factors (RIF) and partial correlation and information (PCIT) analysis.
Article in BMC genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed, 35 citations in OpenAlex.
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- Unraveling the Role of Bromodomain and Extra-Terminal Proteins in Human Uterine Leiomyosarcoma.Cells · 2024Article
- Transcriptomic signatures of progressive and regressive liver fibrosis and portal hypertension.iScience · 2024Article
- Expression network analysis of bovine skin infested with Rhipicephalus australis identifies pro-inflammatory genes contributing to tick susceptibility.Scientific reports · 2024Article
- Identification of candidate regulatory genes for intramuscular fatty acid composition in pigs by transcriptome analysis.Genetics, selection, evolution : GSE · 2024Article
- Soybean molasses increases subcutaneous fat deposition while reducing lipid oxidation in the meat of castrated lambs.Journal of animal science · 2024Article
- Hematological Normality, Serum Biochemistry, and Acute Phase Proteins in Healthy Beef Calves in the Brazilian Savannah.Animals : an open access journal from MDPI · 2023Article
- An Exploratory Data Analysis from Ovine and Bovine RNA-Seq Identifies Pathways and Key Genes Related to Cervical Dilatation.Animals : an open access journal from MDPI · 2023Article
- Gene Functional Networks from Time Expression Profiles: A Constructive Approach Demonstrated in Chili Pepper (Plants (Basel, Switzerland) · 2023Article
- EEF1A1 transcription cofactor gene polymorphism is associated with muscle gene expression and residual feed intake in Nelore cattle.Mammalian genome : official journal of the International Mammalian Genome Society · 2022Article
- A Hybrid Machine Learning and Network Analysis Approach Reveals Two Parkinson's Disease Subtypes from 115 RNA-Seq Post-Mortem Brain Samples.International journal of molecular sciences · 2022Article
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundFinding meaningful gene-gene interaction and the main Transcription Factors (TFs) in co-expression networks is one of the most important challenges in gene expression data mining.
resultsHere, we developed the R package "CeTF" 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. To demonstrate the CeTF package application, we analyzed gastric cancer RNA-seq data obtained from TCGA (The Cancer Genome Atlas) and found the HOXB3 gene as the second most relevant TFs with a high regulatory impact (TFs-HRi) regulating gene pathways in the cell cycle.
conclusionThis preliminary finding shows the potential of CeTF to list master regulators of gene networks. CeTF was designed as a user-friendly tool that provides many highly automated functions without requiring the user to perform many complicated processes. It is available on Bioconductor ( http://bioconductor.org/packages/CeTF ) and GitHub ( http://github.com/cbiagii/CeTF ).
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