exp2gcn {BioNERO} | R Documentation |
Reconstruct gene coexpression network from gene expression
exp2gcn( exp, net_type = "signed", module_merging_threshold = 0.8, SFTpower = NULL, cor_method = "spearman", verbose = FALSE )
exp |
A gene expression data frame with genes in row names and samples in column names or a 'SummarizedExperiment' object. |
net_type |
Network type. One of 'signed', 'signed hybrid' or 'unsigned'. Default: 'signed'. |
module_merging_threshold |
Correlation threshold to merge similar modules into a single one. Default: 0.8. |
SFTpower |
SFT power generated by the function |
cor_method |
Correlation method. One of "pearson", "biweight" or "spearman". Default is "spearman". |
verbose |
Logical indicating whether to display progress messages or not. Default: FALSE. |
List containing:
Adjacency matrix
Data frame of module eigengenes
Data frame of genes and their corresponding modules
Data frame of intramodular connectivity
Vector of module assignment
Correlation matrix
Parameters used for network reconstruction
Objects to plot the dendrogram in plot_dendro_and_colors
.
Fabricio Almeida-Silva
adjacency.fromSimilarity
,TOMsimilarity
,standardColors
,labels2colors
,moduleEigengenes
,plotEigengeneNetworks
,mergeCloseModules
,plotDendroAndColors
,intramodularConnectivity
cutreeDynamicTree
data(filt.se) # The SFT fit was previously calculated and the optimal power was 16 gcn <- exp2gcn(filt.se, SFTpower = 18, cor_method = "pearson")