rliger (version 2.2.0)

plotGeneHeatmap: Plot Heatmap of Gene Expression or Factor Loading

Description

Plot Heatmap of Gene Expression or Factor Loading

Usage

plotGeneHeatmap(
  object,
  features,
  cellIdx = NULL,
  slot = c("normData", "rawData", "scaleData", "scaleUnsharedData"),
  useCellMeta = NULL,
  cellAnnotation = NULL,
  featureAnnotation = NULL,
  cellSplitBy = NULL,
  featureSplitBy = NULL,
  viridisOption = "C",
  ...
)
plotFactorHeatmap(
  object,
  factors = NULL,
  cellIdx = NULL,
  slot = c("H.norm", "H"),
  useCellMeta = NULL,
  cellAnnotation = NULL,
  factorAnnotation = NULL,
  cellSplitBy = NULL,
  factorSplitBy = NULL,
  trim = c(0, 0.03),
  viridisOption = "D",
  ...
)

Value

HeatmapList-class object

Arguments

object

A liger object, with data to be plot available.

features, factors

Character vector of genes of interests or numeric index of factor to be involved. features is required, while factors is by default all the factors (reads object recorded k value in uns slot).

cellIdx

Valid index to subscribe cells to be included. See subsetLiger. Default NULL use all cells.

slot

Use the chosen matrix for heatmap. For plotGeneHeatmap, default "normData", alternatively "rawData", "scaleData" or "scaleUnsharedData". For plotFactorHeatmap, default "H.norm", alternatively "H".

useCellMeta

Character vector of available variable names in cellMeta, variables will be added as annotation to the heatmap. Default NULL.

cellAnnotation

data.frame object for using external annotation, with each column a variable and each row is a cell. Row names of this data.frame will be used for matching cells involved in heatmap. For cells not found in this data.frame, NAs will be added with warning. Default NULL.

featureAnnotation, factorAnnotation

Similar as cellAnnotation, while each row would be a gene or factor, respectively. Default NULL.

cellSplitBy

Character vector of variable names available in annotation given by useCellMeta and cellAnnotation. This slices the heatmap by specified variables. Default NULL.

featureSplitBy, factorSplitBy

Similar as cellSplitBy. Default NULL

viridisOption

See option argument of viridis. Default "C" (plasma) for plotGeneHeatmap and "D" (viridis) for plotFactorHeatmap.

...

Arguments passed on to .plotHeatmap

transpose

Logical, whether to "rotate" the heatmap by 90 degrees so that cell information is displayed by row. Default FALSE.

showCellLabel,showFeatureLabel

Logical, whether to show cell barcodes, gene symbols or factor names. Default TRUE for gene/factors but FALSE for cells.

showCellLegend,showFeatureLegend

Logical, whether to show cell or feature legends. Default TRUE. Can be a scalar for overall control or a vector matching with each given annotation variable.

cellAnnColList,featureAnnColList

List object, with each element a named vector of R-interpretable color code. The names of the list elements are used for matching the annotation variable names. The names of the colors in the vectors are used for matching the levels of a variable (factor object, categorical). Default NULL generates ggplot-flavor categorical colors.

scale

Logical, whether to take z-score to scale and center gene expression. Applied after dataScaleFunc. Default FALSE.

baseSize

One-parameter control of all text sizes. Individual text element sizes can be controlled by other size arguments. "Title" sizes are 2 points larger than "text" sizes when being controlled by this.

cellTextSize,featureTextSize,legendTextSize

Size of cell barcode labels, gene/factor labels, or legend values. Default NULL.

cellTitleSize,featureTitleSize,legendTitleSize

Size of titles of the cell slices, gene/factor slices, or the legends. Default NULL.

RColorBrewerOption

When scale = TRUE, heatmap color will be mapped with brewer.pal. This is passed to name. Default "RdBu".

trim

Numeric vector of two numbers. Higher value limits the maximum value and lower value limits the minimum value. Default c(0, 0.03).

Examples

# \donttest{
plotGeneHeatmap(pbmcPlot, varFeatures(pbmcPlot))
plotGeneHeatmap(pbmcPlot, varFeatures(pbmcPlot),
                useCellMeta = c("leiden_cluster", "dataset"),
                cellSplitBy = "leiden_cluster")

plotFactorHeatmap(pbmcPlot)
plotFactorHeatmap(pbmcPlot, cellIdx = pbmcPlot$leiden_cluster %in% 1:3,
                  useCellMeta = c("leiden_cluster", "dataset"),
                  cellSplitBy = "leiden_cluster")
# }