Skip to contents

Generate scatter plot(s) using liger object

Source: R/ggplotting.R, R/visualization.R
plotDimRed.Rd

This function allows for using available cell metadata to build the x-/y-axis. Available per-cell data can be used to form the color/shape annotation, including cell metadata, raw or processed gene expression, and unnormalized or aligned factor loading. Multiple coloring variable is allowed from the same specification of slot, and this returns a list of plots with different coloring values. Users can further split the plot(s) by grouping on cells (e.g. datasets).

some text

Usage

plotDimRed(
  object,
  colorBy = NULL,
  useDimRed = NULL,
  slot = c("cellMeta", "rawData", "normData", "scaleData", "H.norm", "H", "normPeak",
    "rawPeak"),
  colorByFunc = NULL,
  cellIdx = NULL,
  splitBy = NULL,
  shapeBy = NULL,
  titles = NULL,
  ...
)

plotClusterDimRed(object, useCluster = NULL, useDimRed = NULL, ...)

plotDatasetDimRed(object, useDimRed = NULL, ...)

plotByDatasetAndCluster(
  object,
  useDimRed = NULL,
  useCluster = NULL,
  combinePlots = TRUE,
  ...
)

plotGeneDimRed(
  object,
  features,
  useDimRed = NULL,
  log = TRUE,
  scaleFactor = 10000,
  zeroAsNA = TRUE,
  colorPalette = "C",
  ...
)

plotPeakDimRed(
  object,
  features,
  useDimRed = NULL,
  log = TRUE,
  scaleFactor = 10000,
  zeroAsNA = TRUE,
  colorPalette = "C",
  ...
)

plotFactorDimRed(
  object,
  factors,
  useDimRed = NULL,
  trimHigh = 0.03,
  zeroAsNA = TRUE,
  colorPalette = "D",
  ...
)

Arguments

object

A liger object.

colorBy

Available variable name in specified slot to look for color annotation information. See details. Default NULL generates all-black dots.

useDimRed

Name of the variable storing dimensionality reduction result in the cellMeta(object). Default NULL use default dimRed.

slot

Choose the slot to find the colorBy variable. See details. Default "cellMeta".

colorByFunc

Default NULL. A function object that expects a vector/factor/data.frame retrieved by colorBy as the only input, and returns an object of the same size, so that the all color "aes" are replaced by this output. Useful when, for example, users need to scale the gene expression shown on plot.

cellIdx

Character, logical or numeric index that can subscribe cells. Missing or NULL for all cells.

splitBy

Character vector of categorical variable names in cellMeta slot. Split all cells by groupings on this/these variable(s) to produce a scatter plot containing only the cells in each group. Default NULL.

shapeBy

Available variable name in cellMeta slot to look for categorical annotation to be reflected by dot shapes. Default NULL.

titles

Title text. A character scalar or a character vector with as many elements as multiple plots are supposed to be generated. Default NULL.

...

More plot setting arguments. See .ggScatter and .ggplotLigerTheme.

useCluster

Name of variable in cellMeta(object). Default NULL uses default cluster.

combinePlots

Logical, whether to utilize plot_grid to combine multiple plots into one. Default TRUE returns combined ggplot. FALSE returns a list of ggplot.

features, factors

Name of genes or index of factors that need to be visualized.

log

Logical. Whether to log transform the normalized expression of genes. Default TRUE.

scaleFactor

Number to be multiplied with the normalized expression of genes before log transformation. Default 1e4. NULL for not scaling.

zeroAsNA

Logical, whether to swap all zero values to NA so naColor will be used to represent non-expressing features. Default TRUE.

colorPalette

Name of viridis palette. See viridis for options. Default "C" ("plasma") for gene expression and "D" ("viridis") for factor loading.

trimHigh

Number for highest cut-off to limit the outliers. Factor loading above this value will all be trimmed to this value. Default 0.03.

Value

A ggplot object when a single plot is intended. A list of ggplot objects, when multiple colorBy variables and/or splitBy are set. When plotly = TRUE, all ggplot objects become plotly (htmlwidget) objects.

ggplot object when only one feature (e.g. cluster variable, gene, factor) is set. List object when multiple of those are specified.

Details

Available option for slot include: "cellMeta", "rawData", "normData", "scaleData", "H.norm" and "H". When "rawData", "normData" or "scaleData", colorBy has to be a character vector of feature names. When "H.norm" or "H", colorBy can be any valid index to select one factor of interests. Note that character index follows "Factor_[k]" format, with replacing [k] with an integer.

When "cellMeta", colorBy has to be an available column name in the table. Note that, for colorBy as well as x, y, shapeBy and splitBy, since a matrix object is feasible in cellMeta table, using a column (e.g. named as "column1" in a certain matrix (e.g. named as "matrixVar") should follow the syntax of "matrixVar.column1". When the matrix does not have a "colname" attribute, the subscription goes with "matrixVar.V1", "matrixVar.V2" and etc. Use "UMAP.1", "UMAP.2", "TSNE.1" or "TSNE.2" for the 2D embeddings generated with rliger package. These are based on the nature of as.data.frame method on a DataFrame object.

See also

Please refer to plotDimRed, .ggScatter, .ggplotLigerTheme for additional graphic setting

Examples

plotDimRed(pbmcPlot, colorBy = "dataset", slot = "cellMeta",
           labelText = FALSE)
#> ℹ Plotting feature "dataset" on 600 cells
#> ✔ Plotting feature "dataset" on 600 cells ... done
#> 

plotDimRed(pbmcPlot, colorBy = "S100A8", slot = "normData",
           dotOrder = "ascending", dotSize = 2)
#> ℹ Plotting feature "S100A8" on 600 cells
#> ✔ Plotting feature "S100A8" on 600 cells ... done
#> 

plotDimRed(pbmcPlot, colorBy = 2, slot = "H.norm",
           dotOrder = "ascending", dotSize = 2, colorPalette = "viridis")
#> ℹ Plotting feature "Factor_2" on 600 cells
#> ✔ Plotting feature "Factor_2" on 600 cells ... done
#> 

plotClusterDimRed(pbmcPlot)
#> ℹ Plotting feature "leiden_cluster" on 600 cells
#> ✔ Plotting feature "leiden_cluster" on 600 cells ... done
#> 

plotDatasetDimRed(pbmcPlot)
#> ℹ Plotting feature "dataset" on 600 cells
#> ✔ Plotting feature "dataset" on 600 cells ... done
#> 

plotByDatasetAndCluster(pbmcPlot)
#> ℹ Plotting feature "dataset" on 600 cells
#> ✔ Plotting feature "dataset" on 600 cells ... done
#> 
#> ℹ Plotting feature "leiden_cluster" on 600 cells
#> ✔ Plotting feature "leiden_cluster" on 600 cells ... done
#> 

plotGeneDimRed(pbmcPlot, varFeatures(pbmcPlot)[1])
#> ℹ Plotting feature "ISG15" on 600 cells
#> ✔ Plotting feature "ISG15" on 600 cells ... done
#> 

plotFactorDimRed(pbmcPlot, 2)
#> ℹ Plotting feature "Factor_2" on 600 cells
#> ✔ Plotting feature "Factor_2" on 600 cells ... done
#>