plot_variant_influences: Plot cape coefficients
In cape: Combined Analysis of Pleiotropy and Epistasis for Diversity Outbred Mice

View source: R/plot_variant_influences.R

plot_variant_influences

R Documentation

Plot cape coefficients

Description

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.

Usage

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
)

Arguments

`data_obj`	a `Cape` object
`p_or_q`	A threshold indicating the maximum p value (or q value if FDR was used) of significant interactions and main effects
`min_std_effect`	An optional filter. The plot will exclude all pairs with standardized effects below the number set here.
`plot_all_vals`	If TRUE will plot all values regardless of significant
`standardize`	Whether to plot effect sizes (FALSE) or standardized effect sizes (TRUE)
`color_scheme`	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.
`pos_col`	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`
`neg_col`	The color to use for negative main effects and interactions takes the same values as pos_col.
`not_tested_col`	The color to use for marker pairs not tested. Takes the same values as pos_col and neg_col
`show_marker_labels`	Whether to write the marker labels on the plot
`show_chr`	Whether to show chromosome boundaries
`label_chr`	Whether to label chromosomes if plotted
`show_alleles`	If TRUE, the allele of each marker is indicated by color.
`scale_effects`	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.
`pheno_width`	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.
`covar_width`	See pheno_width. This is the same effect for covariates.
`covar_labels`	Labels for covariates if different from those stored in the data object.
`phenotype_labels`	Labels for traits if different from those stored in the data object
`show_not_tested`	Whether to color the marker pairs that were not tested. If FALSE, they will not be colored in.