Biological Network Reconstruction Omnibus


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Documentation for package ‘BioNERO’ version 1.0.4

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check_SFT Check scale-free topology fit for a given network
consensus_modules Identify consensus modules across independent data sets
consensus_SFT_fit Pick power to fit networks to scale-free topology
consensus_trait_cor Correlate set-specific modules and consensus modules to sample information
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 enrichment analysis for a set of genes
exp2gcn Reconstruct gene coexpression network from gene expression
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_edge_list Get edge list from an adjacency matrix for a group of genes
get_HK Get housekeeping genes from global expression profile
get_hubs_gcn Get GCN hubs
get_hubs_grn Get hubs for gene regulatory network
get_hubs_ppi 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_netrep Calculate module preservation between two expression data sets using NetRep's algorithm
modPres_WGCNA Calculate module preservation between two expression data sets using WGCNA'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
PC_correction Apply Principal Component (PC)-based correction for confounding artifacts
plot_dendro_and_colors Plot dendrogram of genes and modules
plot_dendro_and_cons_colors Plot dendrogram of genes and consensus 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_grn Plot gene regulatory network from edge list
plot_heatmap Plot heatmap of hierarchically clustered sample correlations or gene expression
plot_ngenes_per_module Plot number of genes per module
plot_PCA Plot Principal Component Analysis (PCA) of samples
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
SFT_fit Pick power to fit network to a scale-free topology
ZKfiltering Filter outlying samples based on the standardized connectivity (Zk) method
zma.interpro Maize Interpro annotation
zma.se Maize gene expression data from Shin et al., 2021.
zma.tfs Maize transcription factors