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
Lysosome	5	5476 1522 5660 1509 537	C=121;O=5;E=0.20;R=25.46;rawP=1.67e-06;adjP=1.67e-05
Gastric acid secretion	3	7430 476 3784	C=74;O=3;E=0.12;R=24.98;rawP=0.0002;adjP=0.0010
Glycosaminoglycan biosynthesis - chondroitin sulfate	2	56548 79586	C=22;O=2;E=0.04;R=56.01;rawP=0.0006;adjP=0.0020
Vibrio cholerae infection	2	3784 537	C=54;O=2;E=0.09;R=22.82;rawP=0.0035;adjP=0.0076
Pathogenic Escherichia coli infection	2	7430 84617	C=56;O=2;E=0.09;R=22.00;rawP=0.0038;adjP=0.0076
Protein digestion and absorption	2	476 3784	C=81;O=2;E=0.13;R=15.21;rawP=0.0077;adjP=0.0128
Pancreatic secretion	2	476 3784	C=101;O=2;E=0.16;R=12.20;rawP=0.0118;adjP=0.0169
Phagosome	2	84617 537	C=153;O=2;E=0.25;R=8.05;rawP=0.0258;adjP=0.0323
Protein processing in endoplasmic reticulum	2	10961 10956	C=165;O=2;E=0.27;R=7.47;rawP=0.0296;adjP=0.0329
Metabolic pathways	5	3242 51604 79586 537 3939	C=1130;O=5;E=1.83;R=2.73;rawP=0.0366;adjP=0.0366

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).