Generates a data frame containing network topology information from either a pre-built graph object or directly from an adjacency matrix.
Usage
get_network_topology(
graph_obj = NULL,
graph_obj_list = NULL,
mat = NULL,
graph_mat_list = NULL,
transfrom.method = c("none", "scale", "center", "log2", "log10", "ln", "rrarefy",
"rrarefy_relative"),
r.threshold = 0.7,
p.threshold = 0.05,
method = c("WGCNA", "SpiecEasi", "SPARCC", "cor"),
cor.method = c("pearson", "kendall", "spearman"),
proc = c("holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none"),
SpiecEasi.method = c("mb", "glasso"),
sparcc_R = 20,
bootstrap = 100
)Arguments
- graph_obj
An graph object from build_graph_from_mat or build_graph_from_df. The network object to be visualized.
- graph_obj_list
A list of graph objects. Optional alternative to
graph_obj. Each element is analyzed separately.- mat
Numeric Matrix (default = NULL) The matrix to build graph_obj
- graph_mat_list
A list of matrices corresponding to
graph_obj_list. Optional. Each element is paired with the graph object at the same position and used for topology analysis separately.- transfrom.method
Character. Data transformation methods applied before correlation analysis. Options include: "none" (raw data), "scale" (z-score standardization), "center" (mean centering only), "log2" (log2 transfrom), "log10" (log10 transfrom), "ln" (natural transfrom ), "rrarefy" (random rarefaction using
vegan::rrarefy), "rrarefy_relative" (rarefy then convert to relative abundance).- r.threshold
Numeric. Correlation coefficient threshold; edges are kept only if |r| >= r.threshold.
- p.threshold
Numeric. Significance threshold for correlations; edges are kept only if p < p.threshold.
- method
Character. Relationship analysis methods. Options include: "WGCNA", "SpiecEasi", "SPARCC" and "cor".
- cor.method
Character. Correlation analysis method. Options include "pearson", "kendall", and "spearman".
- proc
Character. Correlation p-value adjustment methods. Options include: "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", and "none".
- sparcc_R
Integer. Number of bootstrap/permutation replicates for SparCC p-values (when
method = "SPARCC"). Default 20.- bootstrap
Numeric (default = 100). Number of bootstrap iterations for stability analysis