View source: R/graph_outputs.R
color_biplot_by_channels | R Documentation |
Colors points of a biplot (2d-tSNE, 2d-PCA...) by the intensity of channels for each flowframe in the flowset
color_biplot_by_channels(
matrix,
x_axis,
y_axis,
global_across_channels = T,
palette = c("blue", "green", "red"),
resolution = 72,
data_transformation_reverse = identity,
file_name = "biplot.pdf",
raster.height = 480,
raster.width = 480,
...
)
matrix |
A matrix |
x_axis |
The column name of the x_axis. Usually the same name you used previously in fs.append |
y_axis |
The column name of the y_axis. Usually the same name you used previously in fs.append |
global_across_channels |
Boolean specificying whether the color key should be calibrated across all channels or individually per channel. |
palette |
A vector of colors that'll be passed to colorRampPalette |
resolution |
The resolution of the files that'll be imported in the pdf. Default is 72, increase for higher resolution |
data_transformation_reverse |
The colors will be linearly scaled across the range of the data. If the data was transformed, you may however want the labels which appear in your color-keys to reflect the raw intensities. In this case, this should be the inverse of the function you used to transform your data |
file_name |
String of the location of the output file (should end in .pdf) |
raster.height |
height of each embedded raster. Defaults to 480 |
raster.width |
Width of each embedded raster. Defaults to 480 |
... |
passed to plot (suggested: pch=16, cex=0.5 or less) |
Since pdf files are vectorized, they can get really big if a lot of data point are plotted. This function thus used bitmap images that are stored in a temporary directory (tmpDir()) and then import them in a single pdf. If you're interested in using the bitmap images, you can fetch them in tmpDir()
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