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:

- 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`.

### 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 1.0.4 Index]