| name | bioconductor-kegggraph |
| description | KEGGGraph is an interface between KEGG pathway and graph object as well as a collection of tools to analyze, dissect and visualize these graphs. It parses the regularly updated KGML (KEGG XML) files into graph models maintaining all essenti |
| when_to_use | Use when: KGML Parsing: Parsing local or remote KGML (KEGG XML) files into standard R graphNEL objects using parseKGML2Graph.; Pathway Dissection: Subsetting complex pathways into smaller subgraphs based on node types (using subGraphByNodeType) or specific neighborhoods (using subKEGGgraph).; Graph Merging: Combining multiple related pathways (e.g., signaling pathways) into a single unified network using me. Not for: For dynamic visualization, interactive navigation, and manual editing of KEGG pathway diagrams, use KGML-ED instead.; For performing Signaling Pathway Impact Analysis directly without manual graph manipulation, use SPIA instead.; For modern ggplot2-b |
| user-invocable | false |
KEGGgraph
Dependencies & Environment
Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.
- Version: 1.72.0 · Bioconductor: 3.23 · R: ≥ 4.6
- Imports: XML, graph, RCurl, Rgraphviz
- Install:
BiocManager::install("KEGGgraph")
When to Use
- KGML Parsing: Parsing local or remote KGML (KEGG XML) files into standard R
graphNEL objects using parseKGML2Graph.
- Pathway Dissection: Subsetting complex pathways into smaller subgraphs based on node types (using
subGraphByNodeType) or specific neighborhoods (using subKEGGgraph).
- Graph Merging: Combining multiple related pathways (e.g., signaling pathways) into a single unified network using
mergeGraphs.
- Topology Analysis: Calculating graph characteristics like in-degrees, out-degrees, or betweenness centrality (via
brandes.betweenness.centrality from RBGL) on biological pathways.
When NOT to Use
- For dynamic visualization, interactive navigation, and manual editing of KEGG pathway diagrams, use
KGML-ED instead.
- For performing Signaling Pathway Impact Analysis directly without manual graph manipulation, use
SPIA instead.
- For modern
ggplot2-based visualization of KEGG pathways, use ggkegg instead because KEGGgraph relies on Rgraphviz for rendering.
Data Requirements
- KGML Files: Local KGML files or a valid internet connection to fetch them remotely via
retrieveKGML.
- Node Identifiers: Input data must align with KEGG standards (e.g., Entrez Gene IDs) to map correctly to the parsed graph nodes.
Key Parameters
- genesOnly (FALSE): Logical passed to
parseKGML2Graph; if TRUE, non-gene nodes (like compounds or maps) are removed from the graph.
- expandGenes (TRUE): Logical passed to
parseKGML2Graph or KEGGpathway2Graph; if TRUE, nodes representing multiple homologues are topologically expanded.
- organism ("hsa"): Three-letter KEGG organism code used in
retrieveKGML.
- destfile: File path to save the remotely retrieved KGML file when using
retrieveKGML.
Best Practices
- Expand Gene Nodes: Set
expandGenes=TRUE when parsing to ensure that nodes representing multiple gene products (homologues) are expanded into individual nodes.
- Merge Related Pathways: Use
mergeGraphs to union related pathways together, which helps resolve disconnected nodes that lack edges in a single specific disease pathway.
- Translate Identifiers: Use
translateGeneID2KEGGID to map Entrez Gene IDs from microarray data to KEGG IDs before performing graph operations.
- Subset for Clarity: Use
subKEGGgraph to divide and conquer large pathways, maintaining KEGG information while subsetting the graph.
Common Pitfalls
- Disconnected Nodes: Disease pathways often contain genes with a degree of 0 because their interaction partners are in other pathways; fix this by using
mergeGraphs to combine linked pathways.
- Grouped Homologues: A single node in KEGG may represent multiple homologues (e.g., MAPK1 and MAPK3); fix this by setting
expandGenes=TRUE during parsing.
- Identifier Mismatch: Microarray data uses Entrez IDs but the graph uses KEGG IDs; fix this by using
translateGeneID2KEGGID or translateKEGGID2GeneID.
Alternatives
- SPIA: A package implementing the Signaling Pathway Impact Analysis algorithm that internally uses pathway topology but requires less manual graph manipulation.
- KGML-ED: A standalone tool designed for the dynamic visualization, interactive navigation, and editing of KEGG pathway diagrams.
Citations
- Zhang, J. D., & Wiemann, S. (2009). KEGGgraph: a graph approach to KEGG PATHWAY in R and Bioconductor. Bioinformatics, 25(11), 1470-1471.
References
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