ScatterplotCellScoreComponents {CellScore} | R Documentation |
This function will plot the components of the CellScore, namely the donor- like and the target-like scores. The function will only plot the scores for the test samples (annotated by the cellscore$column sub_cell_type1). Standards are not included.
ScatterplotCellScoreComponents(cellscore, cell.change, index.plot = FALSE)
cellscore |
a data.frame of CellScore values as calculated by CellScore() |
cell.change |
a data.frame with 3 columns: start cell type, test cell type, target cell type |
index.plot |
a logical variable, with TRUE meaning sample index should be plotted for easy identification of spots. Default is FALSE. This is useful if you want to see where the samples are located on the plot. |
This function outputs the plot on the active graphical device and returns invisibly NULL.
CellScore
for details on CellScore.
## Load the expression set for the standard cell types library(Biobase) library(hgu133plus2CellScore) # eset.std ## Locate the external data files in the CellScore package rdata.path <- system.file("extdata", "eset48.RData", package = "CellScore") tsvdata.path <- system.file("extdata", "cell_change_test.tsv", package = "CellScore") if (file.exists(rdata.path) && file.exists(tsvdata.path)) { ## Load the expression set with normalized expressions of 48 test samples load(rdata.path) ## Import the cell change info for the loaded test samples cell.change <- read.delim(file= tsvdata.path, sep="\t", header=TRUE, stringsAsFactors=FALSE) ## Combine the standards and the test data eset <- combine(eset.std, eset48) ## Generate cosine similarity for the combined data ## NOTE: May take 1-2 minutes on the full eset object ## so we subset it for 4 cell types pdata <- pData(eset) sel.samples <- pdata$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) ## Make the scaterplot of CellScore components ScatterplotCellScoreComponents(cellscore, cell.change, FALSE) }