spatial_hsv_plot | R Documentation |
Colors spots on an an ST array grid according to a 'feature' (i.e. gene expression (raw counts or scaled) and features available in the meta data slot). NOTE that this function only draws a plot for one sample at the time.
spatial_hsv_plot( object, features, split.hsv = FALSE, sample.index = 1, rescale = TRUE, spots = NULL, type = NULL, min.cutoff = NA, max.cutoff = NA, slot = "data", pt.size = 2, pt.alpha = 1, pt.border = FALSE, add.alpha = FALSE, palette = NULL, cols = NULL, grid.ncol = NULL, dark.theme = FALSE, sample.label = TRUE, show.sb = TRUE, value.scale = c("samplewise", "all"), verbose = FALSE, ... )
object |
Seurat object |
features |
|
split.hsv |
Should the HSV colored features be split into separate plots? [default: FALSE] |
sample.index |
Index specifying the sample that you want to use for plotting |
rescale |
Rescale each feature column separately from 0 to 1 range. If set to FALSE, all feature columns will be scaled together from 0 to 1 and preserve the relative differencies |
spots |
Character vector with spot IDs to plot [default: all spots] |
type |
Image type to plot on. Here you can specify any of the images available in your Seurat object. To get this list you can
run the |
min.cutoff |
Vector of minimum and maximum cutoff values for each feature, may specify quantile in the form of 'q##' where '##' is the quantile (eg, 'q1', 'q10'). This can be useful if you have outlier values that skew the colorscale in the plot. For example, if you specify 'q1', you will trim of values below the 1st percentile. [default: no cuttoffs] |
max.cutoff |
Vector of minimum and maximum cutoff values for each feature, may specify quantile in the form of 'q##' where '##' is the quantile (eg, 'q1', 'q10'). This can be useful if you have outlier values that skew the colorscale in the plot. For example, if you specify 'q1', you will trim of values below the 1st percentile. [default: no cuttoffs] |
slot |
Which slot to pull expression data from? [dafault: 'data'] |
pt.size |
Point size of each ST spot [default: 1] |
pt.alpha |
Opacity of each ST spot [default: 1] |
pt.border |
Should a border be drawn around the spots? [default: TRUE] |
add.alpha |
Scale spot opacity by selected feature. Higher values get more opaque while lower values make spots transparent. |
palette |
Color palette used for spatial heatmap (see |
cols |
A vector of colors to use for colorscale, e.g. |
grid.ncol |
Number of columns for display when combining plots. This option will only have an effect on the sample level structure. |
dark.theme |
Switches color of scalebar to 'white' |
sample.label |
Should the sample label be included in the image? [default: TRUE] |
show.sb |
Should a scalebar be drawn? [default: TRUE] |
value.scale |
Defines how the dimensionality reduction values should be mapped to the colorbar. 'value.scale = "samplewise"' will scale each feature independantly while 'value.scale = "all"' will use the same value range for all vectors |
verbose |
Print messages |
... |
Extra parameters passed on to |
A ggplot object
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