km2gcn
km2gcn is an R package that enhances the widely used Weighted Gene Co-expression Network Analysis (WGCNA) by incorporating k-means clustering as an additional processing step. This method improves the partitioning of gene co-expression networks (GCNs) into clusters of genes, known as modules. The authors demonstrate that applying k-means clustering after the conventional WGCNA process results in better network partitions, as evidenced by fewer misplaced genes, increased counts of replicable clusters across different tissues, improved enrichment of Gene Ontology terms, and more accurate partitions in simulated data.
Topic
Statistics and probability;Gene expression;Biological networks
Detail
Operation: Gene expression clustering
Software interface: Library
Language: R
License: Not stated
Cost: Free of charge
Version name: -
Credit: The UK Medical Research Council (MRC).
Input: -
Output: -
Contact: Juan A. Botía j.botia@ucl.ac.uk
Collection: -
Maturity: -
Publications
- An additional k-means clustering step improves the biological features of WGCNA gene co-expression networks.
- Botía JA, et al. An additional k-means clustering step improves the biological features of WGCNA gene co-expression networks. An additional k-means clustering step improves the biological features of WGCNA gene co-expression networks. 2017; 11:47. doi: 10.1186/s12918-017-0420-6
- https://doi.org/10.1186/s12918-017-0420-6
- PMID: 28403906
- PMC: PMC5389000
Download and documentation
Documentation: https://github.com/juanbot/km2gcn/blob/master/README.md
Home page: https://github.com/juanbot/km2gcn
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