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T_collapse()
This function aggregates the abundance data at a specified taxonomic level. It accepts a phyloseq object or a data.frame as input.
TaxGroup()
TaxGroup
abs_mat()
Abundances matrix function
cor_degree_abs()
Correlation between degree and abundance Graphing Pearson correlation between degree and abundance.
ctr_df()
The function ctr_df generates a data.frame containing the degree of nodes for each layer.
ctr_g()
This function assigns colors to the network nodes based on their centrality measurements.
ctr_ml()
Colors the nodes according to their centrality.
diff_nodes_graph()
This function identifies the most abundant taxa and distinguishes between nodes with statistically significant differences in their abundance (red) and those without (blue).
g_abundance()
This function assigns colors to the nodes based on their relative abundance.
log2fc()
Quantifies and compares Log Fold Change value between chosen layers.
ml_TaxGroup()
Generating a data.frame of node degrees per layer.
ml_properties()
Multilayer network properties
net_inference()
This function infers a co-abundance network from an abundance table.
net_plot()
This function creates a network plot. This function also provides options for customizing network visualizations, allowing users to adjust node sizes, edge weights, and color schemes to highlight specific patterns or relationships of interest.
node_color_mat()
This function creates a matrix containing the assigned colors for the nodes of a multilayer network.
phyl_ctr_df()
This function generates a data.frame containing the summed centrality values at a specified taxonomic level.
phyl_ctr_plot()
This function displays the centrality measure of each phylum.
slope_R2()
This function computes the slope and R-squared values of a linear-regression for topological properties from networks.
v_colored()
Assign a color to each node of a network depending of a certain taxonomic level, for example, the phylum.
v_colored_ml()
v_colored_ml