PolarCoordHeterPlot {MetabolomicsBasics}

PolarCoordHeterPlot.

Description

PolarCoordHeterPlot will draw a plot in polar coordinates visualizing heterosis effects according to a layout by Swanson-Wagner, where plot radius represents log2 of fold change between lowest and highest genotype and plot angle represents the ratio between lowest, intermediate and highest genotype.

Usage

PolarCoordHeterPlot(
  x,
  gt = c("P1", "P1xP2", "P2"),
  rev_log = NULL,
  exp_fac = 1,
  thr = 1,
  plot_lab = c("none", "text", "graph"),
  col = NULL
)

Arguments

x

Data matrix with measurement values (traits in rows and genotypes in columns).

gt

Character vector of length=3 indicating P1, F and P2. These are used to filter by column name from x.

rev_log

If you've log transformed your data, you might want to revert the log transformation.

exp_fac

Expansion factor to increase figure size.

thr

Alpha level used in ANOVA to filter insignificant rows. Keep thr=1 to include all matrix rows.

plot_lab

Show 'text' or 'graph' style labels of the polar sections (or keep 'none' to omit).

col

Provide a color vector of length nrow(x).

Details

See examples.

Value

Will generate a plot in polar coordinates and return the x/y coordinates of the data points invisibly.

Examples

# using the provided experimental data
raw <- MetabolomicsBasics::raw
sam <- MetabolomicsBasics::sam
x <- t(raw)
colnames(x) <- sam$GT
gt <- c("B73","B73xMo17","Mo17")
PolarCoordHeterPlot(x=x, gt=gt, plot_lab="graph", thr=0.01, rev_log=exp(1))

coord <- PolarCoordHeterPlot(x=x, gt=gt, thr=0.01, rev_log=exp(1))
points(x=coord$x[3], coord$y[3], pch=22, cex=4, col=2)
# using random data
gt <- c("P1","P1xP2","P2")
set.seed(0)
x <- matrix(rnorm(150), nrow = 10, dimnames = list(paste0("M",1:10), sample(rep(gt, 5))))
x[1:4,1:6]
PolarCoordHeterPlot(x=x, gt=gt)
# using text style labels for the sections
PolarCoordHeterPlot(x=x, gt=gt, plot_lab="text", exp_fac=0.75)
# reverting the order of parental genotypes
PolarCoordHeterPlot(x=x, gt=c("P2","P1xP2","P1"), plot_lab="text", exp_fac=0.75)
# using graph style labels for the sections
PolarCoordHeterPlot(x=x, gt=c("P2","P1xP2","P1"), plot_lab="graph")
# coloring data points
PolarCoordHeterPlot(x=x, gt=gt, col=1:10)
# applying ANOVA P value threshold to input rows
PolarCoordHeterPlot(x=x, gt=gt, col=1:10, thr=0.5)
PolarCoordHeterPlot(x=x, gt=gt, plot_lab="graph", col=1:10, thr=0.5)