Enrichr Algorithm

Purpose and Usage

• Scenario 1: Enrichment analysis of significantly differentially expressed genes obtained from SDAS DEG analysis

  SDAS geneSetEnrichment enrichr \
  -i de_t-test.anno_rctd.SmoothMuscle-vs-Endo.sig_filtered.csv -o outdir \
  --species human

• Scenario 2: Enrichment analysis of significantly differentially expressed genes using only databases of interest

  SDAS geneSetEnrichment enrichr \
  -i de_t-test.anno_rctd.SmoothMuscle-vs-Endo.sig_filtered.csv -o outdir \
  --gmt sdas_deg_enrichment/lib/GSEADB/KEGG_2021_Human.gmt

Input Parameter Description

Enrichr Parameter	Required	Default Value	Description
-i / --input	Yes		Enrichr uses significance deg csv file.
-o / --output	Yes		The GSEApy output directory. Default: the current working directory
--species	No	human	Use biuld-in gmt database: human or mouse. Default: human. More database see here: https://amp.pharm.mssm.edu/modEnrichr.
--gmt	No		Enrichr library name(s) required. Separate each name by ",". Default use --species build-in database.
--cut_off	No	1	Adjust-Pval cutoff, used for generating plots. Default: 0.05.
--background	No		Choose background from one of the following. (1) A BioMart Dataset name, e.g. 'hsapiens_gene_ensembl' . (2) A total gene number, e.g. 20000. Only works for GMT file input. (3) A text file contains the background gene list (one gene per row). Gene identifier should be the same to your input (-i). (4) Default: None. It means all genes in the (-g) input as the background.
--top_term	No	10	Numbers of top terms shown in the plot. Default: 10
-v / --verbose	No		Increase output verbosity, print out progress of your job. Default False

Output Results Display

Enrichr Result File	Description
enrichment_{database}.UP.csv	Enrichment analysis results for upregulated genes
enrichment_{database}.DOWN.csv	Enrichment analysis results for downregulated genes
enrichment_{database}.pdf/png	Bar plot of top enriched pathways for up/down genes

• Enrichment analysis results for up/downregulated genes: enrichment_{database}.UP/DOWN.csv are the result files for enrichment analysis of up- and downregulated genes, respectively. The files contain the columns Gene_set, Term, Overlap, P-value, Adjusted P-value, Odds Ratio, Combined Score, Genes, representing the database name, specific pathway name, number and proportion of overlapping genes in the input list, original p-value, adjusted p-value, odds ratio, combined score, and the specific overlapping gene names in the input list.

Gene_set	Term	Overlap	P-value	Adjusted P-value	Odds Ratio	Combined Score	Genes
KEGG_2021_Human.gmt	ABC transporters	43/45	0.00026880161509715636	0.002529897553855589	5.888896293211162	48.41577841510133	ABCA3;ABCB4;...
KEGG_2021_Human.gmt	AGE-RAGE signaling pathway in diabetic complications	90/100	0.00011055669162020043	0.0013606977430178514	2.928493469422023	26.678523151510976	AKT1;PLCB1;...
KEGG_2021_Human.gmt	AMPK signaling pathway	107/120	6.61066069653723e-05	0.0009525689822440243	2.709298083129859	26.074940028325518	AKT1;CREB3;...
...	...	...	...	...	...	...	...

• Enrichment analysis result bar plot: enrichment_{database}.pdf/png. Different colors represent the top enriched pathways for up- and downregulated genes.