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
Proteasome	10	5689 5684 7979 5701 10213 51371 5685 5686 5691 5718	C=44;O=10;E=0.12;R=83.77;rawP=3.34e-17;adjP=4.34e-16
Spliceosome	8	6636 6637 6629 10286 6633 11017 83443 4116	C=127;O=8;E=0.34;R=23.22;rawP=2.36e-09;adjP=1.53e-08
Ubiquitin mediated proteolysis	4	140739 6921 7334 7322	C=135;O=4;E=0.37;R=10.92;rawP=0.0005;adjP=0.0022
Ribosome biogenesis in eukaryotes	3	10775 6880 55505	C=80;O=3;E=0.22;R=13.82;rawP=0.0014;adjP=0.0046
Homologous recombination	2	6742 7979	C=28;O=2;E=0.08;R=26.33;rawP=0.0026;adjP=0.0068
Regulation of autophagy	2	64422 115201	C=34;O=2;E=0.09;R=21.68;rawP=0.0039;adjP=0.0085
Basal transcription factors	2	6880 2958	C=37;O=2;E=0.10;R=19.92;rawP=0.0046;adjP=0.0085
RNA transport	3	10775 4116 7341	C=151;O=3;E=0.41;R=7.32;rawP=0.0082;adjP=0.0133
Shigellosis	2	81873 7322	C=61;O=2;E=0.17;R=12.09;rawP=0.0120;adjP=0.0173
Oxidative phosphorylation	2	9296 5464	C=132;O=2;E=0.36;R=5.58;rawP=0.0502;adjP=0.0653

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).