cape (version 3.1.0)

get_network: Convert the final results to an adjacency matrix.

Description

This function converts the significant cape interactions to an adjacency matrix, which is then used by plot_network

Usage

get_network(
  data_obj,
  geno_obj,
  p_or_q = 0.05,
  min_std_effect = 0,
  standardize = FALSE,
  collapse_linked_markers = TRUE,
  threshold_power = 1,
  verbose = FALSE,
  plot_linkage_blocks = FALSE
)

Arguments

data_obj

a Cape object

geno_obj

a genotype object

p_or_q

A threshold indicating the maximum adjusted p value considered significant. If an fdr method has been used to correct for multiple testing, this value specifies the maximum q value considered significant.

min_std_effect

This numerical value offers an additional filtering method. If specified, only interactions with standardized effect sizes greater then the min_std_effect will be returned.

standardize

A logical value indicating whether the values returned in the adjacency matrix should be effect sizes (FALSE) or standardized effect sizes (TRUE). Defaults to FALSE.

collapse_linked_markers

A logical value. If TRUE markers are combined into linkage blocks based on correlation. If FALSE, each marker is treated as an independent observation.

threshold_power

A numerical value indicating the power to which to raise the marker correlation matrix. This parameter is used in linkage_blocks_network to determine soft thresholding in determining linkage block structure. Larger values result in more splitting of linkage blocks. Smaller values result in less splitting. The default value of 1 uses the unmodified correlation matrix to determine linkage block structure.

verbose

A logical value indicating whether to print algorithm progress to standard out.

plot_linkage_blocks

A logical value indicating whether to plot heatmaps showing the marker correlation structure and where the linkage block boundaries were drawn.

Value

This function returns the data object with an adjacency matrix defining the final cape network based on the above parameters. The network is put into the slot collapsed_net if collapse_linked_markers is set to TRUE, and full_net if collapse_linked_markers is set to FALSE. run_cape automatically requests both networks be generated.

Examples

# NOT RUN {
data_obj <- get_network(data_obj, geno_obj)
# }
# NOT RUN {
# }