CeTF: Coexpression for Transcription Factors using Regulatory Impact Factors and Partial Correlation and Information Theory analysis

This package provides the necessary functions for performing the Partial Correlation coefficient with Information Theory (PCIT) (Reverter and Chan 2008) and Regulatory Impact Factors (RIF) (Reverter et al. 2010) algorithm. The PCIT algorithm identifies meaningful correlations to define edges in a weighted network and can be applied to any correlation-based network including but not limited to gene co-expression networks, while the RIF algorithm identify critical Transcription Factors (TF) from gene expression data. These two algorithms when combined provide a very relevant layer of information for gene expression studies (Microarray, RNA-seq and single-cell RNA-seq data).

Package details

AuthorCarlos Alberto Oliveira de Biagi Junior [aut, cre], Ricardo Perecin Nociti [aut], Breno Osvaldo Funicheli [aut], João Paulo Bianchi Ximenez [ctb], Patrícia de Cássia Ruy [ctb], Marcelo Gomes de Paula [ctb], Rafael dos Santos Bezerra [ctb], Wilson Araújo da Silva Junior [aut, ths]
Bioconductor views ChIPSeq Coverage DifferentialExpression GeneExpression ImmunoOncology Microarray Network Normalization RNASeq Regression Sequencing SingleCell Transcription
MaintainerCarlos Alberto Oliveira de Biagi Junior <cbiagijr@gmail.com>
LicenseGPL-3
Version1.2.4
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("CeTF")

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CeTF documentation built on Nov. 25, 2020, 2 a.m.