The set enrichment analysis allows you to find underlying association in your data in over 130 categories including pathways, molecular function, diseases, etc. This article goes into how to interpret the output from a set enrichment analysis.
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A visible item on the platform, such as a [link] or a [button], is in square brackets.
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2. Click on the [Find Related] tab to access the different categories for the enrichment analysis for the list of concepts selected in the [Data Selection] section.
3. Select a category. More categories can be accessed by clicking the [Select a Category] button.
4. A results table appears showing the enrichment results sorted by p value.
- The p value is calculated based on the Fisher's exact test to determine if there is a significant difference between two proportions for a certain characteristic.
- The proportion in your selected set is compared to a background set which can be determine by the user. Refer to this article on how to set the background for an enrichment analysis.
5. The description for each column in the result table is provided here:
- Concept name: name of the concept belonging to that category
- Number of concepts: number of concepts from your selected data that is part of the concept name
- Type: the Fisher's exact test is two-sided where over-representation is labeled as 'ENRICHED' and under-representation is labeled as 'DEPLETED'
- Concepts in category: number of concepts that belong to this concept name as annotated by the platform
- P-value: Fisher's exact test p value, which is adjusted for multiple testing correction using the Benjamini-Hochberg procedure.
Note: Results that don't pass the false discovery rate of 0.05 are highlighted in red.
6. Click the [Show all] button located in the top right corner to show full results from the enrichment analysis .