plot.info {qtl} R Documentation

## Plot the proportion of missing genotype information

### Description

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

### Usage

```plot.info(x, chr, method=c("both","entropy","variance"), ...)
```

### Arguments

 `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`.

### Details

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.

### Value

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.

### Author(s)

Karl W Broman, kbroman@jhsph.edu

`plot.scanone`, `plot.missing`

### Examples

```data(hyper)

hyper <- calc.genoprob(hyper, step=2.5, off.end=5)
plot.info(hyper,chr=c(1,4))

# save the results and view maximum missing info on each chr
info <- plot.info(hyper)
summary(info)
```

[Package qtl version 0.98-57 Index]