Function to visualise the pairing of parental homologues across the population using graph, with nodes to denote parental homologues and edges to denote deviations from expected proportions under a polysomic model of inheritance
visualisePairing(
meiosis_report.ls,
pos.col = "red",
neg.col = "blue",
parent,
max.lwd = 20,
datawidemax,
add.label = TRUE,
return.data = FALSE,
...
)
If return.data = TRUE
, the values for pairwise deviations from the expected numbers are
returned, useful for determining the value datawidemax
to provide consistent scaling across multiple plots
List output of function meiosis_report
Colour corresponding to excess of pairing associations predicted (positive deviations), by default red
Colour corresponding to lack of pairing associations predicted (negative deviations), by default blue
The parent, either "P1" (mother) or "P2 (father)
Maximum line width, by default 20
This argument is currently a work-around to allow multiple plots to have the same scale (line thicknesses consistent).
No default is provided. To estimate this value, simply set argument return.data = TRUE
, and record the
maximum absolute value over columns 'count', which are the deviations from random expectations. This should be done
over multiple function calls if e.g. comparing both P1 and P2 values. When a global maximum (absolute) deviation is known,
re-run the function with this value for datawidemax
. The line width specified by max.lwd
will then be
used for this, and all other line widths re-scaled accordingly.
Should a label be applied, giving the maximum deviation in the plot? By default TRUE
Should plot data be returned? By default FALSE
Optional arguments passed to plot.igraph
data("mr.ls")
visualisePairing(meiosis_report.ls = mr.ls,
parent = "P1",
datawidemax = 3)
Run the code above in your browser using DataLab