plot_coef | R Documentation |
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,
col = qtl2::CCcolors,
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.
CCcolors, plot_scan1()
, plot_snpasso()
# 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"))
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