HeatmapPlots: Heatmap Plots

In seriph78/COTAN: COexpression Tables ANalysis

Heatmap Plots

Description

These functions create heatmap COEX plots.

Usage

heatmapPlot(genesLists, sets, conditions, dir, pValueThreshold = 0.01)

genesHeatmapPlot(
  objCOTAN,
  primaryMarkers,
  secondaryMarkers = vector(mode = "character"),
  pValueThreshold = 0.01,
  symmetric = TRUE
)

cellsHeatmapPlot(objCOTAN, cells = NULL, clusters = NULL)

plotTheme(plotKind = "common", textSize = 14L)

Arguments

genesLists	A list of genes' arrays. The first array defines the genes in the columns
sets	A numeric array indicating which fields in the previous list should be used
conditions	An array of prefixes indicating the different files
dir	The directory in which are all COTAN files (corresponding to the previous prefixes)
pValueThreshold	The p-value threshold. Default is 0.01
objCOTAN	a COTAN object
primaryMarkers	A set of genes plotted as rows
secondaryMarkers	A set of genes plotted as columns
symmetric	A Boolean: default TRUE. When TRUE the union of primaryMarkers and secondaryMarkers is used for both rows and column genes
cells	Which cells to plot (all if no argument is given)
clusters	Use this clusterization to select/reorder the cells to plot
plotKind	a string indicating the plot kind
textSize	axes and strip text size (default=14)

Details

heatmapPlot() creates the heatmap of one or more COTAN objects

genesHeatmapPlot() is used to plot an heatmap made using only some genes, as markers, and collecting all other genes correlated with these markers with a p-value smaller than the set threshold. Than all relations are plotted. Primary markers will be plotted as groups of rows. Markers list will be plotted as columns.

cellsHeatmapPlot() creates the heatmap plot of the cells' COEX matrix

plotTheme() returns the appropriate theme for the selected plot kind. Supported kinds are: "common", "pca", "genes", "UDE", "heatmap", "GDI", "UMAP", "size-plot"

Value

heatmapPlot() returns a ggplot2 object

genesHeatmapPlot() returns a ggplot2 object

cellsHeatmapPlot() returns the cells' COEX heatmap plot

plotTheme() returns a ggplot2::theme object

See Also

ggplot2::theme() and ggplot2::ggplot()

Examples

data("test.dataset")
objCOTAN <- COTAN(raw = test.dataset)
objCOTAN <- clean(objCOTAN)
objCOTAN <- estimateDispersionNuBisection(objCOTAN, cores = 6L)
objCOTAN <- calculateCoex(objCOTAN, actOnCells = FALSE)
objCOTAN <- calculateCoex(objCOTAN, actOnCells = TRUE)

## Save the `COTAN` object to file
data_dir <- tempdir()
saveRDS(objCOTAN, file = file.path(data_dir, "test.dataset.cotan.RDS"))

## some genes
primaryMarkers <- c("g-000010", "g-000020", "g-000030")

## an example of named list of different gene set
groupMarkers <- list(G1 = primaryMarkers,
                     G2 = c("g-000300", "g-000330"),
                     G3 = c("g-000510", "g-000530", "g-000550",
                            "g-000570", "g-000590"))

hPlot <- heatmapPlot(genesLists = groupMarkers, sets = c(2, 3),
                     pValueThreshold = 0.05, conditions = c("test.dataset"),
                     dir = paste0(data_dir, "/"))
plot(hPlot)

ghPlot <- genesHeatmapPlot(objCOTAN, primaryMarkers = primaryMarkers,
                           secondaryMarkers = groupMarkers,
                           pValueThreshold = 0.05, symmetric = FALSE)
plot(ghPlot)

clusters <- c(rep_len("1", getNumCells(objCOTAN)/2),
              rep_len("2", getNumCells(objCOTAN)/2))
names(clusters) <- getCells(objCOTAN)

chPlot <- cellsHeatmapPlot(objCOTAN, clusters = clusters)
plot(chPlot)

theme <- plotTheme("pca")

seriph78/COTAN documentation built on May 2, 2024, 11:17 a.m.