plot.info: Plot the proportion of missing information in the genotype data

Description

Plot a measure of the proportion of missing information in the genotype data.

Usage

plot.info(x,chr,which=c("both","entropy","variance"),return.result=FALSE,...)

Arguments

An object of class cross. See read.cross for details.

chr

Vector specifying which chromosomes to plot.

which

Indicates whether to plot the entropy version of the information, the variance version, or both.

return.result

If TRUE, returns the results (as a data.frame).

...

Ignored at this point.

Value

Calls plot.scanone to plot the proportion of missing information in the genotype data. If return.result is TRUE, the results are returned as a data.frame with class scanone.

Details

The entropy version of the missing information: for a single individual at a single genomic position, we measure the information as $H = \sum_g p_g \log p_g / \log n$, where $p_g$ is the probability of the genotype $g$, and $n$ is the number of possible genotypes. This takes values between 0 and 1, assuming the value 0 when the genotypes are equally likely and 1 when one genotype has probability 0. We calculate the missing information at a particular position as the average of $H$ across individuals. For an intercross, we don't scale by $\log n$ but by the entropy in the case of genotype probabilities (1/4, 1/2, 1/4). The variance version of the missing information: we calculate the average, across individuals, of the variance of the genotype distribution at a particular locus, and scale by the maximum such variance.

Calculations are done in C, for the sake of speed in the presence of little thought about programming efficiency.

Examples

Run this code

data(hyper)
hyper <- calc.genoprob(hyper,step=2,off.end=10)
plot.info(hyper)