This page provides information regarding major tools used for Keystone Discovery Analysis in metagenomic data.
| Tool Name | Description | PubMed ID |
|---|---|---|
| MENA | Builds ecological networks to identify keystone species using topological properties like degree and betweenness centrality. | 22646978 |
| Cytoscape | General-purpose network analysis tool with plugins for microbiome-specific keystone analysis using centrality measures. | 20656902 |
| CoNet | Constructs co-occurrence networks to identify key taxa based on association measures (Spearman, Pearson, Bray-Curtis). | 27853510 |
| SparCC | Identifies robust correlations in microbiome compositional data to infer keystone species. | 23028285 |
| XGBoost | Machine learning-based feature importance analysis for keystone taxa identification. | ACM |
| Boruta | Feature selection method for identifying keystone taxa from microbiome data. | JStatSoft |
| IndVal | Indicator species analysis to identify taxa strongly associated with environmental conditions. | NSO |
| LEfSe | Differential abundance analysis to detect keystone taxa across microbiome samples. | 21702898 |
| iCAMP | Uses phylogenetic-based null models to identify keystone taxa and their ecological assembly roles. | 32948774 |
| PICRUSt2 | Predicts functional contributions of taxa to infer keystone species based on their metabolic potential. | 32483366 |
| FAPROTAX | Links taxonomy to functional roles, helping identify metabolically important keystone species. | 27634532 |
| HACK Index | A health-associated core keystone index for the human gut microbiome. | 40023840 |
| NetCoMi | Network construction and comparison for microbiome data in R. | 33264391 |
| SPIEC-EASI | Inference and analysis of SPIEC-EASI microbiome networks. | 33161547 |