MAIN KEGG FILE RESULTS

	WEB-based GEne SeT AnaLysis Toolkit

	*Translating gene lists into biological insights...*

User data and parameters: User data: textAreaUpload.txt, Organism: hsapiens, Id Type: ensembl_gene_stable_id, Ref Set: entrezgene, Significance Level: Top10, Statistics Test: Hypergeometric, MTC: BH, Minimum: 2

This table lists the enriched KEGG pathways, number of Entrez IDs in your user data set for the pathway, the corresponding Entrez IDs, and the statistics for the enriched pathway.
The statistic column lists:

C: the number of reference genes in the category
O: the number of genes in the gene set and also in the category
E: the expected number in the category
R: ratio of enrichment
rawP: p value from hypergeometric test
adjP: p value adjusted by the multiple test adjustment

Finally, the pathway name is linked to KEGG where the user ids are highlighted, the number of user gene ids is linked to a table with information about the user ids, and the Entrez IDs are linked to Entrez Gene.

PathwayName	#Gene	EntrezGene	Statistics
Toxoplasmosis	3	8651 4792 5322	C=132;O=3;E=0.19;R=15.56;rawP=0.0010;adjP=0.0040
Pathways in cancer	4	7855 2034 4792 8313	C=326;O=4;E=0.48;R=8.40;rawP=0.0013;adjP=0.0040
Wnt signaling pathway	3	5613 7855 8313	C=150;O=3;E=0.22;R=13.69;rawP=0.0014;adjP=0.0040
Insulin signaling pathway	3	5613 5564 8651	C=138;O=3;E=0.20;R=14.88;rawP=0.0011;adjP=0.0040
Apoptosis	3	5613 4792 11213	C=87;O=3;E=0.13;R=23.61;rawP=0.0003;adjP=0.0040
MAPK signaling pathway	4	11221 5613 5322 10912	C=268;O=4;E=0.39;R=10.22;rawP=0.0007;adjP=0.0040
Arachidonic acid metabolism	2	5322 247	C=59;O=2;E=0.09;R=23.21;rawP=0.0034;adjP=0.0064
Basal cell carcinoma	2	7855 8313	C=55;O=2;E=0.08;R=24.89;rawP=0.0030;adjP=0.0064
Taste transduction	2	5613 3745	C=52;O=2;E=0.08;R=26.33;rawP=0.0027;adjP=0.0064
Adipocytokine signaling pathway	2	5564 4792	C=68;O=2;E=0.10;R=20.13;rawP=0.0045;adjP=0.0076

WebGestalt is currently developed and maintained by Jing Wang and Bing Zhang at the Zhang Lab. Other people who have made significant contribution to the project include Dexter Duncan, Stefan Kirov, Zhiao Shi, and Jay Snoddy.

Funding credits: NIH/NIAAA (U01 AA016662, U01 AA013512); NIH/NIDA (P01 DA015027); NIH/NIMH (P50 MH078028, P50 MH096972); NIH/NCI (U24 CA159988); NIH/NIGMS (R01 GM088822).