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_protein-coding, 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
Spliceosome 12 6427 84950 27316 29896 6431 7307 6432 6434 1655 6428 220988 6426 C=127;O=12;E=1.06;R=11.34;rawP=7.10e-10;adjP=2.84e-08
Cytokine-cytokine receptor interaction 14 3976 1440 6347 3569 6355 2921 3576 6372 2919 2920 8793 3553 355 5008 C=265;O=14;E=2.21;R=6.34;rawP=5.05e-08;adjP=1.01e-06
Malaria 7 1440 3553 6347 3569 6401 3383 3576 C=51;O=7;E=0.42;R=16.47;rawP=2.09e-07;adjP=2.79e-06
Rheumatoid arthritis 8 2919 2353 3553 6347 3569 3383 3576 6372 C=91;O=8;E=0.76;R=10.55;rawP=9.29e-07;adjP=9.29e-06
NOD-like receptor signaling pathway 6 2919 2920 3553 6347 3569 3576 C=58;O=6;E=0.48;R=12.42;rawP=8.66e-06;adjP=6.67e-05
African trypanosomiasis 5 3553 3569 6401 3383 355 C=35;O=5;E=0.29;R=17.15;rawP=1.00e-05;adjP=6.67e-05
Chagas disease (American trypanosomiasis) 7 148022 2353 3553 6347 3569 3576 355 C=104;O=7;E=0.87;R=8.08;rawP=2.65e-05;adjP=0.0002
Osteoclast differentiation 6 2353 8061 3553 3726 2354 9021 C=128;O=6;E=1.07;R=5.63;rawP=0.0007;adjP=0.0035
Chemokine signaling pathway 7 2919 2920 6347 6355 2921 3576 6372 C=189;O=7;E=1.57;R=4.45;rawP=0.0011;adjP=0.0049
Toll-like receptor signaling pathway 5 148022 2353 3553 3569 3576 C=102;O=5;E=0.85;R=5.88;rawP=0.0016;adjP=0.0064



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).