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
p53 signaling pathway	3	5054 1026 4616	C=68;O=3;E=0.16;R=18.29;rawP=0.0006;adjP=0.0105
Cell cycle	3	1026 4609 4616	C=124;O=3;E=0.30;R=10.03;rawP=0.0034;adjP=0.0105
ErbB signaling pathway	3	1026 374 4609	C=87;O=3;E=0.21;R=14.30;rawP=0.0012;adjP=0.0105
MAPK signaling pathway	4	4609 4616 7850 3727	C=268;O=4;E=0.65;R=6.19;rawP=0.0041;adjP=0.0105
Alanine, aspartate and glutamate metabolism	2	9945 2752	C=32;O=2;E=0.08;R=25.92;rawP=0.0027;adjP=0.0105
Cytokine-cytokine receptor interaction	4	3459 8809 91 7850	C=265;O=4;E=0.64;R=6.26;rawP=0.0040;adjP=0.0105
Osteoclast differentiation	3	3459 2355 3727	C=128;O=3;E=0.31;R=9.72;rawP=0.0037;adjP=0.0105
Bladder cancer	2	1026 4609	C=42;O=2;E=0.10;R=19.75;rawP=0.0047;adjP=0.0106
Jak-STAT signaling pathway	3	5292 3459 4609	C=155;O=3;E=0.37;R=8.03;rawP=0.0064;adjP=0.0115
Amino sugar and nucleotide sugar metabolism	2	9945 6675	C=48;O=2;E=0.12;R=17.28;rawP=0.0060;adjP=0.0115

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).