Should Protein KEGG Pathway Analysis Prioritize Pathways of Interest or P-Value Rankings?
When conducting protein KEGG pathway annotation and enrichment analysis, pathways can be selected based on two primary criteria:
Selection Based on P-Value Ranking
This is the most widely used approach, where pathways are selected according to statistical significance, typically measured by the P-value. Pathways with lower P-values are considered more statistically significant, indicating a stronger association with the dataset. A common practice is to report and discuss pathways with P-values below predefined thresholds (e.g., 0.05 or 0.01).
Selection Based on Biological Relevance
In certain studies, specific biological processes or pathways may be of primary interest, even if they do not have the lowest P-values. For example, if the research focuses on a particular disease or cellular function, pathways related to these topics may be prioritized regardless of statistical ranking.
A balanced approach often yields the most meaningful results. Initially, P-values can be used to identify statistically significant pathways, followed by further refinement based on biological relevance. Additionally, to mitigate the risk of false positives, applying multiple testing correction methods, such as the false discovery rate (FDR), is recommended.
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