TF_networks: TF_networks.
In ShirinG/exprAnalysis: A package for analysing RNA-seq and expression array data

Description Usage Arguments Details Value Examples

Ceates the input files for TF network analysis using Biolayout3D and Cytoscape.

1 2	TF_networks(expmatrix, nodeAnno, GeneName = "row.names", projectfolder = getwd(), organism = "human", outPrefix = "outPrefix")

`expmatrix`	An input matrix with gene names as row names and sample names as column names.
`nodeAnno`	A data frame with node annotation, e.g. logFC and differential expression (e.g. limma output). Rownames have to correspond to rownames of expmatrix!
`GeneName`	Column name with Gene Symbol to be annotated to TF name.
`projectfolder`	File path where to save the output to. Defaults to working directory. Here, it saves the output to a subfolder called "Networks".
`organism`	Organism. Can be human or mouse. For human, the longer published list of TFs is used; for mouse the shorter list provided by Bonn (for which I don't have any more info on where it comes from).
`outPrefix`	Prefix added to output name.

The .expression matrix of TF expression data will have to be opened with Biolayout3D: Set Minimum Correlation and Correlation metric (by default 0.7 and Pearson). Then choose a suitable correlation coefficient (Graph Degree Distribution should be close to linear). Save the resulting network as a TGF file. Open the TGF file in Cytoscape: Open network from file. Then got to Advanced Options: untick "Use first column names" and add " to "Other:". Now set Column 2 as Source and Column 5 as Target. Then open the node annotation table that was also saved by this function: Open table from file, import data as Node Table Columns. YOu can then customize the look of your network.

A .expression output matrix of gene expression of transcription factors in dataset used as Biolayout3D input. And based on these TFs, it also produces a .txt with node annotations of e.g. logFC and differential expression (e.g. limma output)