plotDimReduceGrid: Mapping the dimensionality reduction plot

In compbiomed/celda: CEllular Latent Dirichlet Allocation

Description

Creates a scatterplot given two dimensions from a data dimensionality reduction tool (e.g tSNE) output.

Usage

plotDimReduceGrid(dim1, dim2, matrix, size, xlab, ylab, color_low, color_mid,
  color_high, var_label)

Arguments

dim1	Numeric vector. First dimension from data dimensionality reduction output.
dim2	Numeric vector. Second dimension from data dimensionality reduction output.
matrix	Numeric matrix. Each row of the matrix will be plotted as a separate facet.
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'.
color_low	Character. A color available from ‘colors()'. The color will be used to signify the lowest values on the scale. Default ’grey'.
color_mid	Character. A color available from 'colors()'. The color will be used to signify the midpoint on the scale.
color_high	Character. A color available from ‘colors()'. The color will be used to signify the highest values on the scale. Default ’blue'.
var_label	Character vector. Title for the color legend.

Value

The plot as a ggplot object

Examples

celda.tsne <- celdaTsne(counts = celda.CG.sim$counts, celda.mod = celda.CG.mod)
plotDimReduceGrid(celda.tsne[,1], celda.tsne[,2], matrix = celda.CG.sim$counts, 
                  xlab = "Dimension1", ylab = "Dimension 2", var_label = "tsne", 
                  size = 1, color_low = "grey", color_mid = NULL, color_high = "blue")

compbiomed/celda documentation built on May 25, 2019, 3:58 a.m.