plotDimReduceModule {celda} | R Documentation

## Plotting Celda module probability on a dimension reduction plot

### Description

Create a scatterplot for each row of a normalized gene expression matrix where x and y axis are from a data dimension reduction tool. The cells are colored by the module probability.

### Usage

    plotDimReduceModule(
      x,
      reducedDimName,
      dim1 = NULL,
      dim2 = NULL,
      useAssay = "counts",
      altExpName = "featureSubset",
      celdaMod,
      modules = NULL,
      rescale = TRUE,
      limits = c(0, 1),
      size = 1,
      xlab = "Dimension_1",
      ylab = "Dimension_2",
      colorLow = "grey90",
      colorHigh = "firebrick1",
      ncol = NULL,
      decreasing = FALSE
    )

    ## S4 method for signature 'SingleCellExperiment'
    plotDimReduceModule(
      x,
      reducedDimName,
      dim1 = NULL,
      dim2 = NULL,
      useAssay = "counts",
      altExpName = "featureSubset",
      modules = NULL,
      rescale = TRUE,
      limits = c(0, 1),
      size = 1,
      xlab = "Dimension_1",
      ylab = "Dimension_2",
      colorLow = "grey90",
      colorHigh = "firebrick1",
      ncol = NULL,
      decreasing = FALSE
    )

    ## S4 method for signature 'ANY'
    plotDimReduceModule(
      x,
      dim1,
      dim2,
      celdaMod,
      modules = NULL,
      rescale = TRUE,
      limits = c(0, 1),
      size = 1,
      xlab = "Dimension_1",
      ylab = "Dimension_2",
      colorLow = "grey90",
      colorHigh = "firebrick1",
      ncol = NULL,
      decreasing = FALSE
    )

### Arguments

`x` | Numeric matrix or a SingleCellExperiment object with the matrix located in the assay slot under `useAssay`. Rows represent features and columns represent cells.
`reducedDimName` | The name of the dimension reduction slot in `reducedDimNames(x)` if `x` is a SingleCellExperiment object. Ignored if both `dim1` and `dim2` are set.
`dim1` | Numeric vector. First dimension from data dimension reduction output.
`dim2` | Numeric vector. Second dimension from data dimension reduction output.
`useAssay` | A string specifying which assay slot to use if `x` is a SingleCellExperiment object. Default "counts".
`altExpName` | The name for the altExp slot to use. Default "featureSubset".
`celdaMod` | Celda object of class "celda_G" or "celda_CG". Used only if `x` is a matrix object.
`modules` | Character vector. Module(s) from celda model to be plotted. e.g. c("1", "2").
`rescale` | Logical. Whether rows of the matrix should be rescaled to [0, 1]. Default TRUE.
`limits` | Passed to scale_colour_gradient. The range of color scale.
`size` | Numeric. Sets size of point on plot. Default 1.
`xlab` | Character vector. Label for the x-axis. Default "Dimension_1".
`ylab` | Character vector. Label for the y-axis. Default "Dimension_2".
`colorLow` | Character. A color available from 'colors()'. The color will be used to signify the lowest values on the scale.
`colorHigh` | Character. A color available from 'colors()'. The color will be used to signify the highest values on the scale.
`ncol` | Integer. Passed to facet_wrap. Specify the number of columns for facet wrap.
`decreasing` | logical. Specifies the order of plotting the points. If `FALSE`, the points will be plotted in increasing order where the points with largest values will be on top. `TRUE` otherwise. If `NULL`, no sorting is performed. Points will be plotted in their current order in `x`. Default `FALSE`.

### Value

The plot as a ggplot object

### Examples

    data(sceCeldaCG)
    sce <- celdaTsne(sceCeldaCG)
    plotDimReduceModule(x = sce,
      reducedDimName = "celda_tSNE",
      modules = c("1", "2"))
    library(SingleCellExperiment)
    data(sceCeldaCG, celdaCGMod)
    sce <- celdaTsne(sceCeldaCG)
    plotDimReduceModule(x = counts(sce),
      dim1 = reducedDim(altExp(sce), "celda_tSNE")[, 1],
      dim2 = reducedDim(altExp(sce), "celda_tSNE")[, 2],
      celdaMod = celdaCGMod,
      modules = c("1", "2"))

[Package celda version 1.8.1 Index]