TRANSCRIPTION TARGET GENE SET ENRICHMENT 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 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:

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 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_CTTTGT_V$LEF1_Q2	10	149076 84838 63935 11176 8861 3183 57178 6601 22838 91748	C=1939;O=10;E=1.80;R=5.56;rawP=8.10e-06;adjP=0.0011
hsa_GGGCGGR_V$SP1_Q6	11	79595 149076 84838 63935 11176 8861 20 9968 22838 26505 10291	C=2891;O=11;E=2.68;R=4.10;rawP=4.52e-05;adjP=0.0026
hsa_MGGAAGTG_V$GABP_B	6	54499 10523 23334 22838 91748 10291	C=744;O=6;E=0.69;R=8.69;rawP=6.02e-05;adjP=0.0026
hsa_V$ARP1_01	3	23334 6601 91748	C=165;O=3;E=0.15;R=19.60;rawP=0.0005;adjP=0.0086
hsa_V$ATF4_Q2	3	11176 20 22838	C=256;O=3;E=0.24;R=12.63;rawP=0.0017;adjP=0.0086
hsa_V$AP2GAMMA_01	3	149076 63935 8861	C=246;O=3;E=0.23;R=13.15;rawP=0.0015;adjP=0.0086
hsa_V$AP1_Q6	3	11176 20 4798	C=253;O=3;E=0.23;R=12.78;rawP=0.0017;adjP=0.0086
hsa_V$FREAC2_01	3	149076 23334 4798	C=255;O=3;E=0.24;R=12.68;rawP=0.0017;adjP=0.0086
hsa_SCGGAAGY_V$ELK1_02	6	79595 54499 7249 10523 23334 10291	C=1176;O=6;E=1.09;R=5.50;rawP=0.0007;adjP=0.0086
hsa_V$NRF2_01	3	54499 10523 23334	C=265;O=3;E=0.25;R=12.21;rawP=0.0019;adjP=0.0086

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).