Plot QTL effects along chromosome
Plot estimated QTL effects along a chromosomes.
plot_coef( x, map, columns = NULL, col = NULL, scan1_output = NULL, add = FALSE, gap = NULL, top_panel_prop = 0.65, legend = NULL, ... ) plot_coefCC( x, map, columns = 1:8, scan1_output = NULL, add = FALSE, gap = NULL, top_panel_prop = 0.65, legend = NULL, ... ) ## S3 method for class 'scan1coef' plot( x, map, columns = 1, col = NULL, scan1_output = NULL, add = FALSE, gap = NULL, top_panel_prop = 0.65, legend = NULL, ... )
x |
Estimated QTL effects ("coefficients") as obtained from
|
map |
A list of vectors of marker positions, as produced by
|
columns |
Vector of columns to plot |
col |
Vector of colors, same length as |
scan1_output |
If provided, we make a two-panel plot with coefficients on top and LOD scores below. Should have just one LOD score column; if multiple, only the first is used. |
add |
If TRUE, add to current plot (must have same map and chromosomes). |
gap |
Gap between chromosomes. The default is 1% of the total genome length. |
top_panel_prop |
If |
legend |
Location of legend, such as |
... |
Additional graphics parameters. |
plot_coefCC() is the same as plot_coef(), but forcing
columns=1:8 and using the Collaborative Cross colors,
CCcolors.
None.
A number of graphics parameters can be passed via .... For
example, bgcolor to control the background color, and things
like ylab and ylim. These are not included as formal
parameters in order to avoid cluttering the function definition.
In the case that scan1_output is provided, col,
ylab, and ylim all control the panel with estimated
QTL effects, while col_lod, ylab_lod, and
ylim_lod control the LOD curve panel.
If legend is indicated so that a legend is shown, legend_lab
controls the labels in the legend, and legend_ncol indicates the
number of columns in the legend.
# read data
iron <- read_cross2(system.file("extdata", "iron.zip", package="qtl2"))
# insert pseudomarkers into map
map <- insert_pseudomarkers(iron$gmap, step=1)
# calculate genotype probabilities
probs <- calc_genoprob(iron, map, error_prob=0.002)
# grab phenotypes and covariates; ensure that covariates have names attribute
pheno <- iron$pheno[,1]
covar <- match(iron$covar$sex, c("f", "m")) # make numeric
names(covar) <- rownames(iron$covar)
# calculate coefficients for chromosome 7
coef <- scan1coef(probs[,7], pheno, addcovar=covar)
# plot QTL effects (note the need to subset the map object, for chromosome 7)
plot(coef, map[7], columns=1:3, col=c("slateblue", "violetred", "green3"))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.