https://github.com/saezlab/gene-network-inference-in-r
Mutual information-based and bicor-based methods for genome-wide reverse engineering of gene regulatory networks in R.
https://github.com/saezlab/gene-network-inference-in-r
Last synced: 7 months ago
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Mutual information-based and bicor-based methods for genome-wide reverse engineering of gene regulatory networks in R.
- Host: GitHub
- URL: https://github.com/saezlab/gene-network-inference-in-r
- Owner: saezlab
- Created: 2021-01-27T19:32:22.000Z (over 5 years ago)
- Default Branch: main
- Last Pushed: 2021-04-04T18:41:11.000Z (over 5 years ago)
- Last Synced: 2025-01-22T07:37:41.204Z (over 1 year ago)
- Homepage:
- Size: 12.3 MB
- Stars: 1
- Watchers: 4
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
## Overview
**net_inf_ARACNE.Rmd** and **net_inf_WGCNA.Rmd** scripts provide mutual information-based and bicor-based methods for the genome-wide reverse engineering of gene regulatory networks, implemented in [Minet R package](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-9-461), and [WGCNA R package](https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/), respectively. Here, we use [ARACNE](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-7-S1-S7) and [WGCNA](https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/) to infer a gene regulatory network from a [data set](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE119931) of 27123 genes and 6 samples. For further details about pre-processing steps (normalization and noise elimination), please refer to https://github.com/saezlab/transcriptutorial/blob/master/scripts/01_normalisation.md.
The **dorothea_int_aracne.Rmd** script is used to extract matching TF-Target ineractions between [Dorothea](https://bioconductor.org/packages/release/data/experiment/html/dorothea.html) and [ARACNE](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-7-S1-S7) inferred regulons.