CeTF: an R/Bioconductor package for transcription factor co-expression networks using regulatory impact factors (RIF) and partial correlation and information (PCIT) analysis

被引：14

作者：

Oliveira de Biagi Jr, Carlos Alberto ^{[1
,2
,3
]}

Nociti, Ricardo Perecin ^{[2
,4
]}

Brotto, Danielle Barbosa ^{[1
,2
]}

Funicheli, Breno Osvaldo ^{[2
]}

Ruy, Patricia de Cassia ^{[2
,5
]}

Bianchi Ximenez, Joao Paulo ^{[2
]}

Alves Figueiredo, David Livingstone ^{[3
,6
]}

Silva Jr, Wilson Araujo ^{[1
,2
,3
,7
]}

机构：

[1] Univ Sao Paulo, Dept Genet, Ribeirao Preto Med Sch, Ribeirao Preto, Brazil

[2] Ctr Cell Based Therapy CEPID FAPESP, Reg Blood Ctr Ribeirao Preto, Natl Inst Sci & Technol Stem Cell & Cell Therapy, Ribeirao Preto, Brazil

[3] IPEC, Inst Canc Res, Guarapuava, Brazil

[4] Univ Sao Paulo, Fac Anim Sci & Food Engn, Dept Vet Med, Lab Mol Morphophysiol & Dev, Pirassununga, Brazil

[5] HCFMRP USP, Ctr Med Genom, Ribeirao Preto, Brazil

[6] Midwest State Univ Parana UNICTR, Dept Med, Guarapuava, Brazil

[7] Univ Sao Paulo, Ctr Integrat Syst Biol CISBi NAP USP, Ribeirao Preto, Brazil

来源：

BMC GENOMICS | 2021年 / 22卷 / 01期

基金：

巴西圣保罗研究基金会;

关键词：

Bioinformatics; R package; R; Transcript factors; Network; EXPRESSION; CANCER;

D O I：

10.1186/s12864-021-07918-2

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

Background: Finding 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. Results: Here, 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. Conclusion: This 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.

引用

页数：8