multi_dittoDimPlotVaryCells {dittoSeq} | R Documentation |
Generates multiple dittoDimPlots, each showing different cells, arranged into a grid.
multi_dittoDimPlotVaryCells( object, var, vary.cells.meta, vary.cells.levels = metaLevels(vary.cells.meta, object), assay = .default_assay(object), slot = .default_slot(object), adjustment = NULL, min = NULL, max = NULL, color.panel = dittoColors(), colors = seq_along(color.panel), show.titles = TRUE, show.allcells.plot = TRUE, allcells.main = "All Cells", show.legend.single = TRUE, show.legend.plots = FALSE, show.legend.allcells.plot = FALSE, nrow = NULL, ncol = NULL, OUT.List = FALSE, ... )
object |
A Seurat or SingleCellExperiment object to work with |
var |
String name of a "gene" or "metadata" (or "ident" for a Seurat Alternatively, can be a vector of same length as there are cells/samples in the |
vary.cells.meta |
String name of a metadata that should be used for selecting which cells to show in each "varycells" plot. REQUIRED. |
vary.cells.levels |
The values/groupings of the |
color.panel, colors, min, max, assay, slot, adjustment, ... |
additional parameters passed to |
show.titles |
Logical which sets whether titles should be added to the individual varycells plots |
show.allcells.plot |
Logical which sets whether an additional plot showing all of the cells should be added. |
allcells.main |
String which adjusts the title of the allcells plot. Default = "All Cells". Set to |
show.legend.single |
Logical which sets whether to add a single legend as an additional plot. Default = TRUE. |
show.legend.plots |
Logical which sets whether or not legends should be plotted in varycells plot. Default = FALSE. |
show.legend.allcells.plot |
Logical which sets whether or a legend should be plotted in the allcells plot. Default = FALSE. |
ncol, nrow |
Integers which set dimensions of the plot grid. |
OUT.List |
Logical which controls whether the list of plots should be returned as a list instead of as a single grid arrangement of the plots. |
This function generates separate dittoDimPlots that show the same target data, but for distinct cells.
Which cells fall into which plot is controlled with the vary.cells.meta
parameter.
When the quoted name of a metadata containing discrete groupings is given to vary.cells.meta
,
the function makes separate plots containing all cells/samples of each grouping.
If plots for only certain groupings of cells are wanted, names of the wanted groupings can be supplied to the vary.cells.levels
input.
The function then appends a plot containing all groupings, titled as "All Cells" (unless otherwise changed with the allcells.main
parameter),
as well as a single legend. Either of these can be turned off with the show.allcells.plot
and show.legend.single
parameters.
Plots are either output in a grid (default) with ncol
columns and nrow
rows,
or alternatively as a simple list of ggplots if OUT.List
is set to TRUE
.
In the list, the varycells plots will be named by the value of vary.cells.meta
that they contain,
the allcells plot will be named "allcells" and the single legend will be named "legend".
Either continuous or discrete var
data can be displayed.
For continuous data, the range of potential values is calculated at the start, and set, so that colors represent the same values accross all plots.
For discrete data, colors used in each plot are adjusted so that colors represent the same groupings accross all plots.
multiple dittoDimPlot ggplot
s either arranged in a grid OR as a list
Daniel Bunis
dittoDimPlot
for the base DimPlot plotting function
multi_dittoDimPlot
for plotting distinct var
s accross plots instead of disctinct cells
# dittoSeq handles bulk and single-cell data quit similarly. # The SingleCellExperiment object structure is used for both, # but all functions can be used similarly directly on Seurat # objects as well. example(importDittoBulk, echo = FALSE) myRNA multi_dittoDimPlotVaryCells(myRNA, "gene1", vary.cells.meta = "clustering") # This function can be used to quickly scan for differences in expression # within or accross clusters/cell types by providing a gene to 'var' multi_dittoDimPlotVaryCells(myRNA, "gene1", vary.cells.meta = "clustering") # This function is also great for generating separate plots of each individual # element of a tsne/PCplot/umap. This can be useful to check for dispersion # of groups that might otherwise be hidden behind other cells/samples. # To do so, set 'var' and 'vary.cells.meta' the same. multi_dittoDimPlotVaryCells(myRNA, "clustering", vary.cells.meta = "clustering") # The function can also be used to quickly visualize how separate clustering # resolutions match up to each other, or perhaps how certain conditions of # cells disperse accross clusters. multi_dittoDimPlotVaryCells(myRNA, "groups", vary.cells.meta = "clustering") # For an alternative method of viewing, and easily quantifying, how discrete # conditions of cells disperse accross clusters, see '?dittoBarPlot' # Note, for displaying expression or scoring of distinct genes or metadata, # use 'multi_dittoDimPlot'. Its split.by variable can then be used to add # a varyCells-like effect.