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_STTTCRNTTT_V$IRF_Q6	9	3620 3627 5696 567 2323 5698 116071 4261 161145	C=186;O=9;E=0.16;R=56.40;rawP=4.76e-14;adjP=2.19e-12
hsa_V$IRF1_01	7	3627 5696 6373 567 2323 5698 161145	C=247;O=7;E=0.21;R=33.03;rawP=1.65e-09;adjP=1.90e-08
hsa_V$IRF2_01	6	3627 5696 567 2323 5698 161145	C=125;O=6;E=0.11;R=55.95;rawP=1.13e-09;adjP=1.90e-08
hsa_V$IRF_Q6	7	3627 5696 3134 567 4261 116071 161145	C=240;O=7;E=0.21;R=34.00;rawP=1.35e-09;adjP=1.90e-08
hsa_V$NFKAPPAB_01	6	4283 3627 6373 481 9308 3659	C=250;O=6;E=0.21;R=27.97;rawP=7.15e-08;adjP=6.58e-07
hsa_V$ICSBP_Q6	5	3620 5696 567 5698 116071	C=246;O=5;E=0.21;R=23.69;rawP=2.18e-06;adjP=1.43e-05
hsa_V$ISRE_01	5	3627 6373 3134 567 116071	C=246;O=5;E=0.21;R=23.69;rawP=2.18e-06;adjP=1.43e-05
hsa_V$IRF7_01	4	3627 5698 116071 161145	C=250;O=4;E=0.21;R=18.65;rawP=6.26e-05;adjP=0.0003
hsa_V$NFKB_Q6	4	4283 3627 481 9308	C=254;O=4;E=0.22;R=18.36;rawP=6.66e-05;adjP=0.0003
hsa_V$NFKB_C	3	3627 972 3659	C=262;O=3;E=0.22;R=13.35;rawP=0.0015;adjP=0.0046

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).