R/data.R

In ShirinG/exprAnalysis: A package for analysing RNA-seq and expression array data

#' Randomly generated expression data (normalized)
#'
#' A dataset containing randomly generated normalized expression data in form for 4 replicates of 4 treatment groups.
#'
#' @format A data frame with 10000 rows and 16 variables. Rownames show gene names, Colnames are samples.
#' \describe{
#'   \item{Ctrl_0}{Treatment Ctrl replicate 1}
#'   \item{Ctrl_1}{Treatment Ctrl replicate 2}
#'   \item{Ctrl_2}{Treatment Ctrl replicate 3}
#'   \item{Ctrl_3}{Treatment Ctrl replicate 4}
#'   \item{TollLPS_0}{Treatment TolLPS replicate 1}
#'   \item{TollLPS_1}{Treatment TolLPS replicate 2}
#'   \item{TollLPS_2}{Treatment TolLPS replicate 3}
#'   \item{TollLPS_3}{Treatment TolLPS replicate 4}
#'   \item{TolS100A8_0}{Treatment TolMRP8/S100A8 replicate 1}
#'   \item{TolS100A8_1}{Treatment TolMRP8/S100A8 replicate 2}
#'   \item{TolS100A8_2}{Treatment TolMRP8/S100A8 replicate 3}
#'   \item{TolS100A8_3}{Treatment TolMRP8/S100A8 replicate 4}
#'   \item{ActLPS_0}{Treatment ActLPS replicate 1}
#'   \item{ActLPS_1}{Treatment ActLPS replicate 2}
#'   \item{ActLPS_2}{Treatment ActLPS replicate 3}
#'   \item{ActLPS_3}{Treatment ActLPS replicate 4}
#' }
#' @source Randomly generated expression data (R)
#' @usage data(expmatrix)
"expmatrix"

#' Randomly generated expression data (raw)
#'
#' A dataset containing randomly generated expression data in form of raw read counts for 4 replicates of 4 treatment groups.
#'
#' @format A data frame with 10000 rows and 16 variables. Rownames show gene names, Colnames are samples.
#' \describe{
#'   \item{Ctrl_0}{Treatment Ctrl replicate 1}
#'   \item{Ctrl_1}{Treatment Ctrl replicate 2}
#'   \item{Ctrl_2}{Treatment Ctrl replicate 3}
#'   \item{Ctrl_3}{Treatment Ctrl replicate 4}
#'   \item{TolLPS_0}{Treatment TolLPS replicate 1}
#'   \item{TolLPS_1}{Treatment TolLPS replicate 2}
#'   \item{TolLPS_2}{Treatment TolLPS replicate 3}
#'   \item{TolLPS_3}{Treatment TolLPS replicate 4}
#'   \item{TolS100A8_0}{Treatment TolMRP8/S100A8 replicate 1}
#'   \item{TolS100A8_1}{Treatment TolMRP8/S100A8 replicate 2}
#'   \item{TolS100A8_2}{Treatment TolMRP8/S100A8 replicate 3}
#'   \item{TolS100A8_3}{Treatment TolMRP8/S100A8 replicate 4}
#'   \item{ActLPS_0}{Treatment ActLPS replicate 1}
#'   \item{ActLPS_1}{Treatment ActLPS replicate 2}
#'   \item{ActLPS_2}{Treatment ActLPS replicate 3}
#'   \item{ActLPS_3}{Treatment ActLPS replicate 4}
#' }
#' @source Randomly generated expression data (R)
#' @usage data(countmatrix)
"countmatrix"

#' Output data frame from diff_limma_pairwise()
#'
#' A dataset containing output data frame from diff_limma_pairwise().
#'
#' @format A data frame with 9956 rows and 8 variables. Rownames show gene names.
#' \describe{
#'   \item{logFC}{log fold change}
#'   \item{CI.L}{left confidence interval}
#'   \item{CI.R}{right confidence interval}
#'   \item{AveExpr}{Average expression}
#'   \item{t}{t statstics}
#'   \item{P.Value}{p-value}
#'   \item{adj.P.Val}{adjusted p-value}
#'   \item{B}{B statistics}
#' }
#' @source Output data frame from diff_limma_pairwise() (R package "exprAnalysis")
#' @usage data(DEgenes_pw)
"DEgenes_pw"


#' Output data frame from diff_limma_pw_unfiltered()
#'
#' A dataset containing output data frame from diff_limma_pw_unfiltered().
#'
#' @format A data frame with 10000 rows and 8 variables. Rownames show gene names.
#' \describe{
#'   \item{logFC}{log fold change}
#'   \item{CI.L}{left confidence interval}
#'   \item{CI.R}{right confidence interval}
#'   \item{AveExpr}{Average expression}
#'   \item{t}{t statstics}
#'   \item{P.Value}{p-value}
#'   \item{adj.P.Val}{adjusted p-value}
#'   \item{B}{B statistics}
#' }
#' @source Output data frame from diff_limma_pw_unfiltered() (R package "exprAnalysis")
#' @usage data(Allgenes_limma_pw)
"Allgenes_limma_pw"


#' Transcription factors from mouse and human
#'
#' A dataset containing transcription factors from mouse and human (from Bonn)
#'
#' @format A data frame with 929 rows and 3 variables. Rownames show gene names.
#' \describe{
#'   \item{Mouse}{Mouse TFs}
#'   \item{Human}{Human TFs}
#'   \item{Merged_Taxa}{Type of TF}
#' }
#' @source Bonner list used for TF networks
#' @usage data(TFs)
"TFs"

#' Transcription factors from human (published list)
#'
#' A dataset containing transcription factors from human (from paper: Automated Identification of Core Regulatory Genes in Human Gene Regulatory Networks. Vipin Narang et al. 2015. PLOS Comp Biol.)
#'
#' @format A data frame with 1374 rows and 3 variables. Rownames show gene names.
#' \describe{
#'   \item{Human}{Human TFs}
#'   \item{NodeType}{0 = TF}
#'   \item{GeneType}{gene type}
#' }
#' @source Automated Identification of Core Regulatory Genes in Human Gene Regulatory Networks. Vipin Narang et al. 2015. PLOS Comp Biol.
#' @usage data(TFs_paper)
"TFs_paper"

#' Module Eigengenes example data
#'
#' A dataset containing module eigengenes example data.
#'
#' @format A data frame with 16 rows and 11 variables. Rownames show sample names.
#' \describe{
#'   \item{MEblue}{Module eigengenes of blue module}
#'   \item{MEbrown}{Module eigengenes of brown module}
#'   \item{MEpink}{TModule eigengenes of pink module}
#'   \item{MEred}{TModule eigengenes of red module}
#'   \item{MEgreen}{TModule eigengenes of green module}
#'   \item{MEmagenta}{TModule eigengenes of magenta module}
#'   \item{MEblack}{TModule eigengenes of black module}
#'   \item{MEyellow}{TModule eigengenes of yellow module}
#'   \item{MEpurple}{TModule eigengenes of purple module}
#'   \item{MEturquoise}{TModule eigengenes of turquoise module}
#'   \item{MEgrey}{TModule eigengenes of grey module}
#' }
#' @source WGCNA example data run.
#' @usage data(MEs)
"MEs"