plot.info {qtl} | R Documentation |
Plot a measure of the proportion of missing information in the genotype data.
plot.info(x, chr, method=c("both","entropy","variance"), ...)
x |
An object of class cross . See
read.cross for details. |
chr |
Vector specifying the chromosomes to plot. |
method |
Indicates whether to plot the entropy version of the information, the variance version, or both. |
... |
Passed to plot.scanone . |
The missing information is calculated using the multipoint genotype
probabilities calculated with calc.genoprob
.
The entropy version of the missing information: for a single individual at a single genomic position, we measure the missing information as H = sum 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, defining 0 log 0 = 0. This takes values between 0 and 1, assuming the value 1 when the genotypes (given the marker data) are equally likely and 0 when the genotypes are completely determined. 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 (conditional on the observed marker data) 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) and the plot is created
by a call to plot.scanone
.
Note that summary.scanone
may be used to display
the maximum missing information on each chromosome.
An object with class scanone
: a data.frame with columns the
chromosome IDs and cM positions followed by the entropy and/or
variance version of the missing information.
Karl W Broman, kbroman@jhsph.edu
data(hyper) hyper <- calc.genoprob(hyper, step=2.5, off.end=5) plot.info(hyper,chr=c(1,4,6,7,15)) # save the results and view maximum missing info on each chr info <- plot.info(hyper) summary(info)