This function plots the the cape coefficients between pairs of markers as a heat map. The interactions are shown in the main part of the heatmap while the main effects are shown on the right hand side. Directed interactions are read from the y axis to the x axis. For example an interaction from marker1 to marker2 will be shown in the row corresponding to marker1 and the column corresponding to marker2. Similarly, if marker1 has a main effect on any traits, these will be shown in the row for marker1 and the trait columns.
plot_variant_influences(
data_obj,
p_or_q = 0.05,
min_std_effect = 0,
plot_all_vals = FALSE,
standardize = FALSE,
color_scheme = c("DO/CC", "other"),
pos_col = "brown",
neg_col = "blue",
not_tested_col = "lightgray",
show_marker_labels = FALSE,
show_chr = TRUE,
label_chr = TRUE,
show_alleles = TRUE,
scale_effects = c("log10", "sqrt", "none"),
pheno_width = NULL,
covar_width = NULL,
covar_labels = NULL,
phenotype_labels = NULL,
show_not_tested = TRUE
)This function invisibly returns the variant influences matrix. shown in the heat map.
a Cape object
A threshold indicating the maximum p value (or q value if FDR was used) of significant interactions and main effects
An optional filter. The plot will exclude all pairs with standardized effects below the number set here.
If TRUE will plot all values regardless of significant
Whether to plot effect sizes (FALSE) or standardized effect sizes (TRUE)
A character value of either "DO/CC" or other indicating the color scheme of main effects. If "DO/CC" allele effects can be plotted with the DO/CC colors.
The color to use for positive main effects and interactions
must be one of "green", "purple", "red", "orange", "blue", "brown", "yellow", "gray"
see get_color
The color to use for negative main effects and interactions takes the same values as pos_col.
The color to use for marker pairs not tested. Takes the same values as pos_col and neg_col
Whether to write the marker labels on the plot
Whether to show chromosome boundaries
Whether to label chromosomes if plotted
If TRUE, the allele of each marker is indicated by color.
One of "log10", "sqrt", "none." If some effects are very large, scaling them can help show contrasts between smaller values. The default is no scaling.
Each marker and trait gets one column in the matrix. If there are many markers, this makes the effects on the traits difficult to see. pheno_width increases the number of columns given to the phenotypes. For example, if pheno_width = 11, the phenotypes will be shown 11 times wider than individual markers.
See pheno_width. This is the same effect for covariates.
Labels for covariates if different from those stored in the data object.
Labels for traits if different from those stored in the data object
Whether to color the marker pairs that were not tested. If FALSE, they will not be colored in.