Standard fold enrichment cut-off/threshold in functional enrichment analysis?

Question

[jjust8200]

I am analyzing a set of DE miRNAs for functional enrichment. I have carried out miRNA target prediction using different algorithms and experimental databases. However, when testing for enrichment in “biological pathways” I get approx. 250 pathways significantly enriched (BH FDR corrected p-value). I recognize that because of the nature of the statistics used, pathways with many genes involved are more easily recognized as significant. Some of the most significant pathways, based on p-value, only have a fold enrichment of 1.4. Is there a standard or biologically meaningful “fold enrichment” cut-off/threshold that is normally implemented in these analysis’?

Thanks in advance

Standard fold enrichment cut-off/threshold in functional enrichment analysis?. Available from: https://www.researchgate.net/post/Standard_fold_enrichment_cut-off_threshold_in_functional_enrichment_analysis [accessed Apr 18, 2017].

[h.mon]

Which methods did you use? Did you see this and this papers?

[jjust8200]

Dear h.mon,

Thank you very much. Those papers are very useful! I will test my data with both algorithms.

I have used the standard hypergeometric distribution to test for enrichment with BH FDR correction of the p-values. I have annotated target genes to both GO, KEGG and REACTOME.

….. however, if the standard enrichment method is used, how would you sort the output – by adjusted p-value or fold enrichment? (of course only including significant KEGG og GO terms).