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: .05, Statistics Test: Hypergeometric, MTC: BH, Minimum: 2

This table lists the enriched transcription factor targets (TFT), number of Entrez IDs in your user data set for the TFT, the corresponding Entrez IDs, and the statistics for the enriched TF.
The statistic column lists:
Finally, 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.

TFT #Gene EntrezGene Statistics
hsa_TCCCRNNRTGC_UNKNOWN 6 25855 80006 8216 113178 80305 64319 C=211;O=6;E=0.35;R=17.03;rawP=1.52e-06;adjP=0.0002
hsa_GGGCGGR_V$SP1_Q6 17 51548 57037 124245 7841 9854 64844 5884 2316 64834 4548 4849 221496 1945 6804 11273 113178 4034 C=2891;O=17;E=4.83;R=3.52;rawP=4.13e-06;adjP=0.0003
hsa_SCGGAAGY_V$ELK1_02 10 57130 51548 55621 57037 205 4849 11051 11129 80209 55336 C=1176;O=10;E=1.96;R=5.09;rawP=2.53e-05;adjP=0.0012
hsa_V$SREBP1_Q6 5 64319 6804 11101 4034 23284 C=245;O=5;E=0.41;R=12.22;rawP=5.83e-05;adjP=0.0016
hsa_V$AP2ALPHA_01 5 55621 9854 64834 64319 23284 C=237;O=5;E=0.40;R=12.64;rawP=4.98e-05;adjP=0.0016
hsa_GGGAGGRR_V$MAZ_Q6 13 163033 51548 9854 64844 5884 4849 64319 200186 1945 11273 4034 10945 23284 C=2250;O=13;E=3.76;R=3.46;rawP=8.09e-05;adjP=0.0019
hsa_CAGGTG_V$E12_Q6 13 80006 57130 9854 84447 2316 64834 64319 11051 11129 1945 6804 155061 4034 C=2450;O=13;E=4.09;R=3.18;rawP=0.0002;adjP=0.0039
hsa_SYATTGTG_UNKNOWN 4 51548 124245 64844 11101 C=231;O=4;E=0.39;R=10.37;rawP=0.0006;adjP=0.0103
hsa_V$AP2GAMMA_01 4 55621 9854 64319 23284 C=246;O=4;E=0.41;R=9.74;rawP=0.0008;adjP=0.0110
hsa_V$ELK1_02 4 51548 55621 84447 11051 C=245;O=4;E=0.41;R=9.78;rawP=0.0008;adjP=0.0110
hsa_V$EGR1_01 4 84447 200186 11273 11101 C=266;O=4;E=0.44;R=9.01;rawP=0.0010;adjP=0.0125
hsa_TGANTCA_V$AP1_C 7 26151 5507 9854 64834 64319 6804 4034 C=1104;O=7;E=1.84;R=3.80;rawP=0.0025;adjP=0.0288
hsa_GKCGCNNNNNNNTGAYG_UNKNOWN 2 124245 25855 C=58;O=2;E=0.10;R=20.65;rawP=0.0043;adjP=0.0456
hsa_V$CP2_02 3 55621 83604 64319 C=253;O=3;E=0.42;R=7.10;rawP=0.0088;adjP=0.0481
hsa_V$CACBINDINGPROTEIN_Q6 3 163033 84447 64319 C=238;O=3;E=0.40;R=7.55;rawP=0.0075;adjP=0.0481
hsa_V$CREB_02 3 124245 25855 10945 C=249;O=3;E=0.42;R=7.22;rawP=0.0085;adjP=0.0481
hsa_V$MZF1_01 3 84447 64319 1945 C=231;O=3;E=0.39;R=7.78;rawP=0.0069;adjP=0.0481
hsa_V$PAX4_03 3 9854 84447 4034 C=249;O=3;E=0.42;R=7.22;rawP=0.0085;adjP=0.0481
hsa_ACTAYRNNNCCCR_UNKNOWN 4 80006 4548 200186 9546 C=444;O=4;E=0.74;R=5.40;rawP=0.0066;adjP=0.0481
hsa_CCAWWNAAGG_V$SRF_Q4 2 2316 83604 C=87;O=2;E=0.15;R=13.77;rawP=0.0094;adjP=0.0481
hsa_V$AP2_Q6_01 3 55621 64319 11129 C=265;O=3;E=0.44;R=6.78;rawP=0.0100;adjP=0.0481
hsa_V$ZIC3_01 3 64319 1945 64710 C=251;O=3;E=0.42;R=7.16;rawP=0.0086;adjP=0.0481
hsa_V$MTF1_Q4 3 57037 9854 11129 C=246;O=3;E=0.41;R=7.30;rawP=0.0082;adjP=0.0481
hsa_V$CP2_01 3 55621 6804 4034 C=258;O=3;E=0.43;R=6.96;rawP=0.0093;adjP=0.0481
hsa_V$MYB_Q6 3 84447 155061 4034 C=253;O=3;E=0.42;R=7.10;rawP=0.0088;adjP=0.0481
hsa_RYAAAKNNNNNNTTGW_UNKNOWN 2 51548 57037 C=84;O=2;E=0.14;R=14.26;rawP=0.0088;adjP=0.0481
hsa_V$HEB_Q6 3 64319 9546 23284 C=263;O=3;E=0.44;R=6.83;rawP=0.0098;adjP=0.0481
hsa_V$ELK1_01 3 200186 11051 9546 C=266;O=3;E=0.44;R=6.76;rawP=0.0101;adjP=0.0481
hsa_V$PEA3_Q6 3 9854 64834 200186 C=253;O=3;E=0.42;R=7.10;rawP=0.0088;adjP=0.0481
hsa_V$EGR_Q6 3 9854 64319 200186 C=273;O=3;E=0.46;R=6.58;rawP=0.0109;adjP=0.0485
hsa_V$AP1_Q2_01 3 26151 9854 4034 C=272;O=3;E=0.45;R=6.61;rawP=0.0107;adjP=0.0485


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).