RugplotCellScore: RugplotCellScore
In CellScore: Tool for Evaluation of Cell Identity from Transcription Profiles

Description Usage Arguments Value See Also Examples

This function will plot a rugplot of all CellScore values for each transition selected in the cell.change data frame. The function will only plot the scores for the test samples (annotated by the cellscore$column sub_cell_type1). Standards are not included. Samples are coloured by a secondary property, which must be a single column in the cellscore data frame.

1	RugplotCellScore(cellscore, cell.change, colour.by = NULL)

`cellscore`	a data.frame of CellScore values as calculated by CellScore().
`cell.change`	a data frame containing three columns, one for the start (donor) test and target cell type. Each row of the data. frame describes one transition from the start to a target cell type.
`colour.by`	the name of the column in the cellscore argument that contains the secondary property.

This function outputs the plot on the active graphical device and returns invisibly NULL.

CellScore for details on CellScore.

## Load the expression set for the standard cell types
library(Biobase)
library(hgu133plus2CellScore) # eset.std

## Locate the external data files in the CellScore package
rdata.path <- system.file("extdata", "eset48.RData", package = "CellScore")
tsvdata.path <- system.file("extdata", "cell_change_test.tsv",
                             package = "CellScore")

if (file.exists(rdata.path) && file.exists(tsvdata.path)) {

   ## Load the expression set with normalized expressions of 48 test samples
   load(rdata.path)

   ## Import the cell change info for the loaded test samples
   cell.change <- read.delim(file= tsvdata.path, sep="\t",
                             header=TRUE, stringsAsFactors=FALSE)

   ## Combine the standards and the test data
   eset <- combine(eset.std, eset48)

   ## Generate cosine similarity for the combined data
   ## NOTE: May take 1-2 minutes on the full eset object
   ## so we subset it for 4 cell types
   pdata <- pData(eset)
   sel.samples <- pdata$general_cell_type %in% c("ESC", "EC", "FIB", "KER", 
                 "ASC", "NPC", "MSC", "iPS", "piPS")
   eset.sub <- eset[, sel.samples]
   cs <- CosineSimScore(eset.sub, cell.change, iqr.cutoff=0.1)

   ## Generate the on/off scores for the combined data
   individ.OnOff <- OnOff(eset.sub, cell.change, out.put="individual")

   ## Generate the CellScore values for all samples
   cellscore <- CellScore(eset.sub, cell.change, individ.OnOff$scores,
                          cs$cosine.samples)

   ## Rugplot of CellScore, colour samples by transition induction method
   RugplotCellScore(cellscore, cell.change,
                    "transition_induction_method")
 }