PlotCosineSimHeatmap {CellScore} | R Documentation |
This function plots a triangular heatmap of the cosine similarity scores.
PlotCosineSimHeatmap(data, desc = "xx", width = 20, height = 20, x = -30, y = 3)
data |
a data.frame of cosine similarity scores, as generated by the function CosineSimScore(). |
desc |
a single character, with description for the file name. Suggested are "general.groups", "subgroups", and "samples". |
width |
the width of the output pdf, in inches. |
height |
the height of the output pdf, in inches. |
x |
the x-position of the heatmap legend. It may be necessary to change the value to position the legend in a suitable place on the plot. |
y |
the y-position of the heatmap legend. It may be necessary to change the value to position the legend in a suitable place on the plot. |
This function will print a pdf of the cosine similarity scores in the current working directory.
CosineSimScore
for details on cosine
similarity calculation.
## 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$general_cell_type %in% c("ESC", "EC", "FIB", "KER", "ASC", "NPC", "MSC") eset.sub <- eset[, sel.samples] cs <- CosineSimScore(eset.sub, cell.change, iqr.cutoff=0.1) ## Generate pdf of cosine similarity heatmap in the working directory PlotCosineSimHeatmap(cs$cosine.general.groups, "general groups", width=7, height=7, x=-3.5, y=1) }