Create a scatterplot based off of a matrix containing the celda state probabilities per cell.
plot_dr_state(dim1, dim2, matrix, rescale = FALSE, xlab = "Dimension_1",
ylab = "Dimension_2", color_low = "grey", color_high = "blue")
Numeric vector; first dimension from data dimensionality reduction output.
Numeric vector; second dimension from data dimensionality reduction output.
Cell state probability matrix, will have cell name for column name and state probability for row name.
Boolean. If TRUE z-score normalize the matrix. Default FALSE.
Character vector, used as label for x axis. Default "Dimension_1".
Character vector, used as label for y axis. Default "Dimension_2".
Character vector of R colors available from the colors() function. The color will be used to signify the lowest values on the scale. Default: 'grey'
Character vector of R colors available from the colors() function. The color will be used to signify the highest values on the scale. Default: 'blue'