exp2gcn {BioNERO}R Documentation

Reconstruct gene coexpression network from gene expression

Description

Reconstruct gene coexpression network from gene expression

Usage

exp2gcn(
  exp,
  net_type = "signed",
  module_merging_threshold = 0.8,
  SFTpower = NULL,
  cor_method = "spearman",
  verbose = FALSE
)

Arguments

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 SFT_fit.

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.

Value

List containing:

Author(s)

Fabricio Almeida-Silva

See Also

adjacency.fromSimilarity,TOMsimilarity,standardColors,labels2colors,moduleEigengenes,plotEigengeneNetworks,mergeCloseModules,plotDendroAndColors,intramodularConnectivity cutreeDynamicTree

Examples

data(filt.se)
# The SFT fit was previously calculated and the optimal power was 16
gcn <- exp2gcn(filt.se, SFTpower = 18, cor_method = "pearson")

[Package BioNERO version 1.2.0 Index]