plotDimReduceGrid {celda} | R Documentation |
Creates a scatterplot given two dimensions from a data dimensionality reduction tool (e.g tSNE) output.
plotDimReduceGrid( dim1, dim2, matrix, size, xlab, ylab, colorLow, colorMid, colorHigh, varLabel, ncol = NULL, headers = NULL )
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'. |
colorLow |
Character. A color available from 'colors()'. The color will be used to signify the lowest values on the scale. Default 'grey'. |
colorMid |
Character. A color available from 'colors()'. The color will be used to signify the midpoint on the scale. |
colorHigh |
Character. A color available from 'colors()'. The color will be used to signify the highest values on the scale. Default 'blue'. |
varLabel |
Character vector. Title for the color legend. |
ncol |
Integer. Passed to facet_wrap. Specify the number of columns for facet wrap. |
headers |
Character vector. If 'NULL', the corresponding rownames are used as labels. Otherwise, these headers are used to label the genes. |
The plot as a ggplot object
data(celdaCGSim, celdaCGMod) celdaTsne <- celdaTsne(counts = celdaCGSim$counts, celdaMod = celdaCGMod) plotDimReduceGrid(celdaTsne[, 1], celdaTsne[, 2], matrix = celdaCGSim$counts, xlab = "Dimension1", ylab = "Dimension2", varLabel = "tsne", size = 1, colorLow = "grey", colorMid = NULL, colorHigh = "blue")