plot.updog: Draw a genotype plot from the output of 'updog'.
In dcgerard/updogAlpha: Using Parental Data for Offspring Genotyping

Description Usage Arguments Details Value Author(s)

If ggplot2 is installed, then this function will use it to make the genotype plot. Otherwise, "classic" R base graphics will be used. The ggplot2 version is made using the function plot_geno. The "classic" R base graphics version is made using the function plot_geno_base.

## S3 method for class 'updog'
plot(x, gg = requireNamespace("ggplot2", quietly = TRUE),
  plot_beta = FALSE, ask = TRUE, use_colorblind = FALSE,
  show_maxpostprob = FALSE, show_ogeno = TRUE, show_outlier = TRUE, ...)

`x`	The output from `updog`.
`gg`	Should we use ggplot2 to plot the genotypes (`TRUE`), or not (`FALSE`). If ggplot2 is present, then this defaults to `TRUE`. If it is not present, then it defaults to `FALSE`.
`plot_beta`	A logical. If true, then we'll plot the estimated beta density of the outlier model, followed by the estimated beta distributions of the overdispersion models.
`ask`	A logical. Should we ask before continuing on to the next plot (`TRUE`) or not (`FALSE`)?
`use_colorblind`	A logical. Should we use a colorblind safe palette (`TRUE`), or not (`FALSE`)?
`show_maxpostprob`	A logical. Should we scale the sizes by `x$maxpostprob` (`TRUE`), or not (`FALSE`)?
`show_ogeno`	A logical. Should we color code by `x$ogeno` (`TRUE`), or not (`FALSE`)?
`show_outlier`	A logical. Should we scale the transparency by `x$prob_ok` (`TRUE`), or not (`FALSE`)?
`...`	Not used.

The returned plot is what we call a "genotype plot". On the x-axis is the number of "a" reads and on the y-axis is the number of "A" reads, where "a" and "A" are the possible alleles. If available, the observations are colorcoded by estimated genotype (via the maximum a posteriori classifier), their transparency is proportional to the the posterior probability that a point is an outlier, and their size is (possibly) scaled by their maximum posterior probability. The lines are defined by the equation

A / (A + a) = p,

where A is the number of "A" reads, a is the number of "a" reads, and p is the proportion of counts we would expect to observe on average given the genotype of an individual, the sequencing error rate, and the read-mapping bias.

If there is parental data, these are also plotted with crosses and plusses. If the parents have larger counts than the offspring, then (at least when gg = TRUE) the parental counts are scaled until they just reach the plot. The scaled parental counts are labeled on the plot with a semi-transparent "(scaled)".

The second plot is the distribution of outlying points.

The third plot contains the underlying beta densities for the different genotypes.

A plot object.

David Gerard

dcgerard/updogAlpha documentation built on May 14, 2019, 3:10 a.m.