Workflow of KEGG Pathway Annotation and Enrichment Analysis

The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis is a widely-used tool in modern biological research, particularly in fields such as genomics, transcriptomics, and metabolomics. The KEGG database aggregates extensive information on genes, compounds, reactions, and their interactions, facilitating the biological annotation of omics data and providing insight into gene function relationships within networks.

 

Data Preprocessing

The initial step in KEGG pathway annotation and enrichment analysis is data preprocessing. For transcriptomics data, standardized gene expression data is commonly used as input, while proteomics or metabolomics data typically uses quantitative protein or metabolite data. Preprocessing includes common procedures such as removing low-quality or outlier values, normalization, and selecting differentially expressed genes (or proteins, metabolites), which ensure data accuracy and reliability, laying a foundation for subsequent analysis.

 

Gene or Metabolite Annotation

Following preprocessing, the next step is to map target genes, proteins, or metabolites to the KEGG database for biological function annotation. This typically involves using existing KEGG IDs or specialized software (e.g., BlastKOALA or GhostKOALA) to annotate species-specific data in KEGG. The annotation process links each gene, protein, or metabolite with a specific KEGG pathway entry, providing information on its functional role within biological networks.

 

Constructing a Pathway Analysis Set

After annotation, the pathway analysis set is constructed by grouping all genes, proteins, or metabolites associated with the target pathways. This process, based on KEGG pathway maps, helps researchers identify biological pathways that may be activated or suppressed under certain biological conditions. Building the pathway analysis set is essential for enrichment analysis.

 

Enrichment Analysis

Enrichment analysis is a critical step in KEGG pathway analysis, aiming to identify pathways significantly enriched under specific conditions. This is commonly achieved using statistical methods, such as hypergeometric tests or Fisher's exact test, which assess overlap between the background set and target set to determine significantly enriched pathways. Pathways are then ranked based on p-values or FDR (False Discovery Rate) adjusted values, producing a list of significantly enriched pathways.

 

Result Visualization

To facilitate interpretation and presentation, enrichment analysis results are typically visualized through bar charts, heatmaps, or network diagrams. Visualization allows researchers to quickly identify key biological pathways and investigate their potential mechanisms and functions.

 

Biological Interpretation

After obtaining the significantly enriched KEGG pathway results, researchers perform biological interpretation to understand their significance under experimental conditions. This step involves in-depth analysis of biological function, considering the study context and relevant literature, providing a basis for subsequent experimental design and theoretical exploration.

 

KEGG pathway annotation and enrichment analysis is a powerful method that involves data preprocessing, annotation, pathway set construction, enrichment analysis, result visualization, and biological interpretation. Through these steps, researchers can systematically reveal the roles of genes or metabolites under specific biological conditions, elucidating biological network relationships and advancing understanding of biological processes and mechanisms.