plotDimReduceFeature {celda} | R Documentation |
Create a scatterplot for each row of a normalized gene expression matrix where x and y axis are from a data dimensionality reduction tool. The cells are colored by expression of the specified feature.
plotDimReduceFeature(dim1, dim2, counts, features, normalize = TRUE, exactMatch = TRUE, trim = c(-2, 2), size = 1, xlab = "Dimension_1", ylab = "Dimension_2", colorLow = "grey", colorMid = NULL, colorHigh = "blue")
dim1 |
Numeric vector. First dimension from data dimensionality reduction output. |
dim2 |
Numeric vector. Second dimension from data dimensionality reduction output. |
counts |
Integer matrix. Rows represent features and columns represent cells. |
features |
Character vector. Uses these genes for plotting. |
normalize |
Logical. Whether to normalize the columns of 'counts'. Default TRUE. |
exactMatch |
Logical. Whether an exact match or a partial match using 'grep()' is used to look up the feature in the rownames of the counts matrix. Default TRUE. |
trim |
Numeric vector. Vector of length two that specifies the lower and upper bounds for the data. This threshold is applied after row scaling. Set to NULL to disable. Default c(-2,2). |
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'. |
The plot as a ggplot object
data(celdaCGSim, celdaCGMod) celdaTsne <- celdaTsne(counts = celdaCGSim$counts, celdaMod = celdaCGMod) plotDimReduceFeature(dim1 = celdaTsne[, 1], dim2 = celdaTsne[, 2], counts = celdaCGSim$counts, features = c("Gene_99"), exactMatch = TRUE)