PC_correction           Apply Principal Component (PC)-based correction
                        for confounding artifacts
SFT_fit                 Pick power to fit network to a scale-free
                        topology
ZKfiltering             Filter outlying samples based on the
                        standardized connectivity (Zk) method
check_SFT               Check scale-free topology fit for a given
                        network
consensus_SFT_fit       Pick power to fit networks to scale-free
                        topology
consensus_modules       Identify consensus modules across independent
                        data sets
consensus_trait_cor     Correlate set-specific modules and consensus
                        modules to sample information
cor2adj                 Calculate an adjacency matrix from a
                        correlation matrix
cormat_to_edgelist      Transform a correlation matrix to an edge list
detect_communities      Detect communities in a network
dfs2one                 Combine multiple expression tables (.tsv) into
                        a single data frame
enrichment_analysis     Perform overrepresentation analysis for a set
                        of genes
exp2cor                 Calculate pairwise correlations between genes
                        in a matrix
exp2gcn                 Infer gene coexpression network from gene
                        expression
exp2gcn_blockwise       Infer gene coexpression network from gene
                        expression in a blockwise manner
exp2grn                 Infer gene regulatory network from expression
                        data
exp_genes2orthogroups   Collapse gene-level expression data to
                        orthogroup level
exp_preprocess          Preprocess expression data for network
                        reconstruction
filt.se                 Filtered maize gene expression data from Shin
                        et al., 2021.
filter_by_variance      Keep only genes with the highest variances
gene_significance       Calculate gene significance for a given group
                        of genes
get_HK                  Get housekeeping genes from global expression
                        profile
get_edge_list           Get edge list from an adjacency matrix for a
                        group of genes
get_hubs_gcn            Get GCN hubs
get_hubs_grn            Get hubs for gene regulatory network
get_neighbors           Get 1st-order neighbors of a given gene or
                        group of genes
grn_average_rank        Rank edge weights for GRNs and calculate
                        average across different methods
grn_combined            Infer gene regulatory network with multiple
                        algorithms and combine results in a list
grn_filter              Filter a gene regulatory network based on
                        optimal scale-free topology fit
grn_infer               Infer gene regulatory network with one of three
                        algorithms
is_singleton            Logical expression to check if gene or gene set
                        is singleton or not
modPres_WGCNA           Calculate module preservation between two
                        expression data sets using WGCNA's algorithm
modPres_netrep          Calculate module preservation between two
                        expression data sets using NetRep's algorithm
module_enrichment       Perform enrichment analysis for coexpression
                        network modules
module_preservation     Calculate network preservation between two
                        expression data sets
module_stability        Perform module stability analysis
module_trait_cor        Correlate module eigengenes to trait
net_stats               Calculate network statistics
og.zma.osa              Orthogroups between maize and rice
osa.se                  Rice gene expression data from Shin et al.,
                        2021.
parse_orthofinder       Parse orthogroups identified by OrthoFinder
plot_PCA                Plot Principal Component Analysis (PCA) of
                        samples
plot_dendro_and_colors
                        Plot dendrogram of genes and modules
plot_eigengene_network
                        Plot eigengene network
plot_expression_profile
                        Plot expression profile of given genes across
                        samples
plot_gcn                Plot gene coexpression network from edge list
plot_gene_significance
                        Plot a heatmap of gene significance
plot_grn                Plot gene regulatory network from edge list
plot_heatmap            Plot heatmap of hierarchically clustered sample
                        correlations or gene expression
plot_module_trait_cor   Plot a heatmap of module-trait correlations
plot_ngenes_per_module
                        Plot number of genes per module
plot_ppi                Plot protein-protein interaction network from
                        edge list
q_normalize             Quantile normalize the expression data
remove_nonexp           Remove genes that are not expressed based on a
                        user-defined threshold
replace_na              Remove missing values in a gene expression data
                        frame
zma.interpro            Maize Interpro annotation
zma.se                  Maize gene expression data from Shin et al.,
                        2021.
zma.tfs                 Maize transcription factors
