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:
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
ECM-receptor interaction 22 1292 1290 1284 2335 375790 9900 1277 1286 7148 6383 9672 1287 7059 3693 1281 7060 1291 1289 1282 1278 960 1311 C=85;O=22;E=1.33;R=16.51;rawP=7.06e-21;adjP=7.98e-19
Protein digestion and absorption 18 1292 1290 1284 1277 1286 1287 7373 1281 1303 5547 1306 1291 1289 23439 1282 1278 1298 2006 C=81;O=18;E=1.27;R=14.18;rawP=4.76e-16;adjP=2.69e-14
Focal adhesion 21 5058 1292 1290 1284 2335 1277 1286 7148 1287 7059 3693 1281 2534 7060 1291 1289 80310 1282 1278 5602 1311 C=200;O=21;E=3.13;R=6.70;rawP=9.36e-12;adjP=3.53e-10
TGF-beta signaling pathway 14 1634 656 7044 90 392255 7060 7043 3398 8454 8646 652 7059 1311 654 C=84;O=14;E=1.32;R=10.63;rawP=5.47e-11;adjP=1.55e-09
Pathways in cancer 20 8643 2736 7480 1284 2335 1286 7976 868 1287 83439 4313 1612 7043 1282 652 7188 5602 1021 54583 2735 C=326;O=20;E=5.11;R=3.91;rawP=2.93e-07;adjP=6.62e-06
Axon guidance 12 2042 5365 5058 8633 2534 57689 2048 6091 6586 9353 25791 2049 C=129;O=12;E=2.02;R=5.93;rawP=9.85e-07;adjP=1.59e-05
Amoebiasis 11 1290 1284 2335 1277 1286 1289 7043 1287 1282 1278 1281 C=106;O=11;E=1.66;R=6.62;rawP=9.36e-07;adjP=1.59e-05
Basal cell carcinoma 7 8643 83439 652 2736 7480 7976 2735 C=55;O=7;E=0.86;R=8.12;rawP=2.38e-05;adjP=0.0003
Hedgehog signaling pathway 7 8643 656 652 2736 7480 654 2735 C=56;O=7;E=0.88;R=7.97;rawP=2.69e-05;adjP=0.0003
Malaria 6 9672 7059 1311 7060 7043 6383 C=51;O=6;E=0.80;R=7.51;rawP=0.0001;adjP=0.0011


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).