Package: CeTF
Type: Package
Title: Coexpression for Transcription Factors using Regulatory Impact Factors 
  and Partial Correlation and Information Theory analysis
Version: 1.15.0
Authors@R: c(person("Carlos Alberto", "Oliveira de Biagi Junior", email = 
  "", role = c("aut", "cre")), person("Ricardo", "Perecin 
  Nociti", email = "", role = c("aut")), person("Breno", 
  "Osvaldo Funicheli", email = " ", role = c("aut")), 
  person("João Paulo", "Bianchi Ximenez", email = "", 
  role = c("ctb")), person("Patrícia", "de Cássia Ruy", email = 
  "", role = c("ctb")), person("Marcelo", "Gomes de Paula", 
  email = "", role = c("ctb")), person("Rafael", "dos 
  Santos Bezerra", email = "", role = c("ctb")), 
  person("Wilson", "Araújo da Silva Junior", email = "", role = 
  c("aut", "ths")))
Description: 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).
Imports: circlize, ComplexHeatmap, clusterProfiler, DESeq2, dplyr, 
  GenomicTools.fileHandler, GGally, ggnetwork, ggplot2, 
  ggpubr, ggrepel, graphics, grid, igraph, Matrix, network, 
  Rcpp, RCy3, stats, SummarizedExperiment, S4Vectors, utils, methods
Suggests: airway, kableExtra, knitr,, rmarkdown, testthat
SystemRequirements: libcurl4-openssl-dev, libxml2-dev, libssl-dev, gfortran, 
  build-essential, libz-dev, zlib1g-dev
Depends: R (>= 4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.3
biocViews: Sequencing, RNASeq, Microarray, GeneExpression, Transcription, 
  Normalization, DifferentialExpression, SingleCell, Network, 
  Regression, ChIPSeq, ImmunoOncology, Coverage
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppArmadillo