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

• Homepage: https://bioconductor.org/packages/KEGGgraph
• Vignette: https://bioconductor.org/packages/release/bioc/vignettes/KEGGgraph/inst/doc/KEGGgraph.pdf

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