View source: R/plot_raw_data.R
plot.onemap | R Documentation |
Shows a heatmap (in ggplot2, a graphic of geom "tile") for raw data.
Lines correspond to markers and columns to individuals.
The function can plot a graph for all marker types, depending of the cross type (dominant/codominant markers, in all combinations).
The function receives a onemap object of class onemap
, reads information
from genotypes from this object, converts it to a long dataframe format
using function melt() from package reshape2() or internal function create_dataframe_for_plot_outcross(), converts numbers from the object
to genetic notation (according to the cross type), then plots the graphic.
If there is more than 20 markers, removes y labels
For outcross populations, it can show all markers together, or it can split them according the segregation
pattern.
## S3 method for class 'onemap' plot(x, all = TRUE, ...)
x |
an object of class |
all |
a TRUE/FALSE option to indicate if results will be plotted together (if TRUE) or splitted based on their segregation pattern. Only used for outcross populations. |
... |
currently ignored |
a ggplot graphic
# library(ggplot2) data(onemap_example_bc) # Loads a fake backcross dataset installed with onemap plot(onemap_example_bc) # This will show you the graph # You can store the graphic in an object, then save it with a number of properties # For details, see the help of ggplot2's function ggsave() g <- plot(onemap_example_bc) data(onemap_example_f2) # Loads a fake backcross dataset installed with onemap plot(onemap_example_f2) # This will show you the graph # You can store the graphic in an object, then save it with a number of properties # For details, see the help of ggplot2's function ggsave() g <- plot(onemap_example_f2) data(onemap_example_out) # Loads a fake full-sib dataset installed with onemap plot(onemap_example_out) # This will show you the graph for all markers plot(onemap_example_out, all=FALSE) # This will show you the graph splitted for marker types # You can store the graphic in an object, then save it. # For details, see the help of ggplot2's function ggsave() g <- plot(onemap_example_out, all=FALSE)
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