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
RNA transport	5	22985 79902 9883 22794 100101267	C=151;O=5;E=0.41;R=12.31;rawP=5.78e-05;adjP=0.0008
Lysine degradation	3	23067 9739 79813	C=44;O=3;E=0.12;R=25.35;rawP=0.0002;adjP=0.0013
Hedgehog signaling pathway	2	27148 1454	C=56;O=2;E=0.15;R=13.28;rawP=0.0100;adjP=0.0433
Phosphatidylinositol signaling system	2	56623 1609	C=78;O=2;E=0.21;R=9.53;rawP=0.0189;adjP=0.0459
mRNA surveillance pathway	2	22985 22794	C=83;O=2;E=0.22;R=8.96;rawP=0.0212;adjP=0.0459
Glycerophospholipid metabolism	2	9489 1609	C=80;O=2;E=0.22;R=9.29;rawP=0.0198;adjP=0.0459
Pyrimidine metabolism	2	5426 5430	C=99;O=2;E=0.27;R=7.51;rawP=0.0294;adjP=0.0541
Metabolic pathways	7	56623 55627 5426 9489 5430 1609 7841	C=1130;O=7;E=3.04;R=2.30;rawP=0.0333;adjP=0.0541
Lysosome	2	23163 26088	C=121;O=2;E=0.33;R=6.15;rawP=0.0423;adjP=0.0601
Spliceosome	2	11338 22985	C=127;O=2;E=0.34;R=5.85;rawP=0.0462;adjP=0.0601

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).