R: Plot phenotype means against genotypes at one or two markers

effectplot {qtl} | R Documentation

## Plot phenotype means against genotypes at one or two markers

### Description

Plot the phenotype means for each group defined by the genotypes at one or two markers (or the values at a discrete covariate).

### Usage

    effectplot(cross, pheno.col=1, mname1, mark1, geno1, mname2, mark2,
               geno2, main, ylim, xlab, ylab, col, add.legend=TRUE,
               legend.lab, draw=TRUE, var.flag=c("pooled","group"))

### Arguments

`cross` | An object of class `cross`.
`pheno.col` | Column number in the phenotype matrix to be drawn in the plot. One may also give a character string matching a phenotype name. Finally, one may give a numeric vector of phenotypes, in which case it must have the length equal to the number of individuals in the cross, and there must be either non-integers or values < 1 or > no. phenotypes; this last case may be useful for studying transformations.
`mname1` | Name for the first marker or pseudomarker. Pseudomarkers (that is, non-marker positions on the imputation grid) may be referred to in a form like `"5@30.3"`, for position 30.3 on chromosome 5.
`mark1` | Genotype data for the first marker. If unspecified, genotypes will be taken from the data in the input cross object, using the name specified in `mname1`.
`geno1` | Optional labels for the genotypes (or classes in a covariate).
`mname2` | Name for the second marker or pseudomarker (optional).
`mark2` | Like `mark1` (optional).
`geno2` | Optional labels for the genotypes (or classes in a covariate).
`main` | Optional figure title.
`ylim` | Optional y-axis limits.
`xlab` | Optional x-axis label.
`ylab` | Optional y-axis label.
`col` | Optional vector of colors for the different line segments.
`add.legend` | A logical value to indicate whether to add a legend.
`legend.lab` | Optional title for the legend.
`draw` | A logical value to indicate generate the plot or not. If FALSE, no figure will be plotted and this function can be used to calculate the group means and standard errors.
`var.flag` | The method to calculate the group variance. "pooled" means to use the pooled variance and "group" means to calculate from individual group.

### Details

In the plot, the y-axis is the phenotype. In the case of one marker, the x-axis is the genotype for that marker. In the case of two markers, the x-axis is for different genotypes of the second marker, and the genotypes of first marker are represented by lines in different colors. Error bars are plotted at +/- 1 SE.

The results of `sim.geno` are used; if they are not available, `sim.geno` is run with `n.draws=16`. The average phenotype for each genotype group takes account of missing genotype data by averaging across the imputations. The SEs take account of both the residual phenotype variation and the imputation error.

### Value

A data.frame containing the phenotype means and standard errors for each group.

### Author(s)

Hao Wu; Karl W Broman, kbroman@biostat.wisc.edu

### See Also

`plotPXG`, `find.marker`, `effectscan`, `find.pseudomarker`

### Examples

    data(fake.f2)

    # impute genotype data
    ## Not run: fake.f2 <- sim.geno(fake.f2, step=5, n.draws=64)

    ########################################
    # one marker plots
    ########################################
    ### plot of genotype-specific phenotype means for 1 marker
    mname <- find.marker(fake.f2, 1, 37) # marker D1M437
    effectplot(fake.f2, pheno.col=1, mname1=mname)

    ### output of the function contains the means and SEs
    output <- effectplot(fake.f2, mname1=mname)
    output

    ### plot a phenotype
    # Plot of sex-specific phenotype means,
    # note that "sex" must be a phenotype name here
    effectplot(fake.f2, mname1="sex", geno1=c("F","M"))
    # alternatively:
    sex <- pull.pheno(fake.f2, "sex")
    effectplot(fake.f2, mname1="Sex", mark1=sex, geno1=c("F","M"))

    ########################################
    # two markers plots
    ########################################

    ### plot two markers
    # plot of genotype-specific phenotype means for 2 markers
    mname1 <- find.marker(fake.f2, 1, 37) # marker D1M437
    mname2 <- find.marker(fake.f2, 13, 24) # marker D13M254
    effectplot(fake.f2, mname1=mname1, mname2=mname2)

    ### plot two pseudomarkers
    #####  refer to pseudomarkers by their positions
    effectplot(fake.f2, mname1="1@35", mname2="13@25")

    #####  alternatively, find their names via find.pseudomarker
    pmnames <- find.pseudomarker(fake.f2, chr=c(1, 13), c(35, 25))
    effectplot(fake.f2, mname1=pmnames[1], mname2=pmnames[2])

    ### Plot of sex- and genotype-specific phenotype means
    mname <- find.marker(fake.f2, 13, 24) # marker D13M254
    # sex and a marker
    effectplot(fake.f2, mname1=mname, mname2="Sex",
               mark2=sex, geno2=c("F","M"))

    # Same as above, switch role of sex and the marker
    # sex and marker
    effectplot(fake.f2, mname1="Sex", mark1=sex,
               geno1=c("F","M"), mname2=mname)

    # X chromosome marker
    mname <- find.marker(fake.f2, "X", 14) # marker DXM66
    effectplot(fake.f2, mname1=mname)

    # Two markers, including one on the X
    mnames <- find.marker(fake.f2, c(13, "X"), c(24, 14))
    effectplot(fake.f2, mname1=mnames[1], mname2=mnames[2])

[Package qtl version 1.41-6 Index]