Function reference • NPATools

All functions

ND(): Network Diffusion

assess_enrichment(): assess enrichment of the top networks

assess_modularity(): Assess modularity

assign_communities(): Assign communities

calc_CC_LCC(): Calculate connected components and largest connected componets

calc_gs_perm(): ES of permutation

calc_gs_sim(): Select the most representative features

calc_p(): Estimation of p values

cmp_top_net_scores(): Compare top networks scores

comm_net(): Create a network of communities

eFDR(): empirical False Discovery Rate

edge_weights(): Function for the assignment of edges weights in order to better visualize the communities

enrichment_map(): Enrichment map

es(): Enrichment Score

exprs_to_cdf(): Gene expression to cdf values

feat_sets_to_occ(): Feature set list to occurrence matrix

filter_gsl(): Filter a gene set list

find_communities(): Find topological communities

functional_cartography(): Calculate participation coefficient and within module degree z-score

gene_sets_to_X0(): Quantify the occurence of gene sets among positive element of X0

get_cdf(): Gene-level cdf estimation

get_cluster_genes(): Get pathway clusters from enrichment map

get_gene_set_clusters(): Get pathway clusters from enrichment map

get_gs_score(): Get a gene set score from Xs matrix

get_kegg_db(): Get KEGG Pathways using KEGGREST

get_nconn_comp(): Extract connected components of at least n vertices

gsea(): Gene Sert Enrichment Analysis

gsea2enrich(): Create a gseaResult instance from Ulisse GSEA result

normalize_adj_mat(): Symmetric Normalization of Adjancency Matrix

normalize_nd(): Normalization of ND steady state values

ora(): Over Representation Analysis

ora1gs(): Hypergeometric test on 1 dataset

ora2enrich(): ora2enrich this function translates the result of an ORA into the DOSE class "enrichResult"

perm_X0(): Permutation of X0

perm_mat(): Permutation of X

perm_vertices(): Permutation of graph vertices

plot_fc(): Plot the functional cartography of the network

plot_gsea_heatmap(): Plot heatmap of GSEA results for multiple runs

plot_modu_trend(): Plot modularity trend

plot_net_enrich(): Plot network enrichment results

plot_network(): Plot a network

plot_network_scores(): Plot the network scoring summary

plot_ora_heatmap(): Plot heatmap of ORA results for multiple runs

plot_score_by_comm(): Boxplots of a score by community

score_networks(): Score the networks composed of a ranked list of genes

score_networks_summary(): Provide a summary score for he networks composed of a ranked list of genes

string.v12.Entrez.ntm.700.400.k3: Interactome derived from STRING db v12.0 igraph object with 17288 genes and 174962 interactions. Only interactions with confidence >=700 and the top 3 interactions with confidence >=400 & < 700 were considered. Confidence score was calculated without textmining, as described at the URL https://string-db.org. Original protein identifiers were mapped to Entrez Gene identifiers using mappings from NCBI Entrez (https://ftp.ncbi.nlm.nih.gov dowload date 2023-09-19) and https://string-db.org

theme_science(): A ggplot2 theme for good looking plots in science

within_module_degree(): Within-module degree