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
DNA replication	4	3978 23649 4176 4174	C=36;O=4;E=0.13;R=31.53;rawP=8.00e-06;adjP=0.0003
Cell cycle	5	8454 994 4176 4174 6502	C=124;O=5;E=0.44;R=11.44;rawP=8.18e-05;adjP=0.0013
MAPK signaling pathway	6	51701 994 93589 7786 5894 3551	C=268;O=6;E=0.94;R=6.35;rawP=0.0004;adjP=0.0043
Hepatitis C	4	10401 5894 1366 3551	C=134;O=4;E=0.47;R=8.47;rawP=0.0013;adjP=0.0104
Small cell lung cancer	3	10401 3551 6502	C=85;O=3;E=0.30;R=10.01;rawP=0.0034;adjP=0.0181
TGF-beta signaling pathway	3	8646 8454 7059	C=84;O=3;E=0.30;R=10.13;rawP=0.0033;adjP=0.0181
Amino sugar and nucleotide sugar metabolism	2	51005 55577	C=48;O=2;E=0.17;R=11.82;rawP=0.0125;adjP=0.0500
Ubiquitin mediated proteolysis	3	10401 8454 6502	C=135;O=3;E=0.48;R=6.31;rawP=0.0123;adjP=0.0500
RIG-I-like receptor signaling pathway	2	340061 3551	C=71;O=2;E=0.25;R=7.99;rawP=0.0262;adjP=0.0532
Cytosolic DNA-sensing pathway	2	340061 3551	C=56;O=2;E=0.20;R=10.13;rawP=0.0168;adjP=0.0532

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).