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_AACTTT_UNKNOWN	28	10424 92949 2649 26249 2119 11069 5362 64093 154 2066 79191 84109 163702 132204 10265 115111 6786 1305 9162 138046 3357 3084 22920 3760 9423 339479 2118 5796	C=1859;O=28;E=4.09;R=6.84;rawP=2.71e-16;adjP=8.43e-14
hsa_CAGGTG_V$E12_Q6	30	660 1952 3786 2649 26249 3856 4878 11069 5362 64093 25841 3664 154 80758 2066 89797 10265 10170 1305 2983 138046 9162 3084 1145 2901 219699 2118 2982 4703 5796	C=2450;O=30;E=5.40;R=5.56;rawP=4.56e-15;adjP=7.09e-13
hsa_CTTTGA_V$LEF1_Q2	17	92949 26509 4878 2119 93035 10395 54102 2066 132204 89797 6532 1305 112574 138046 3357 3084 8292	C=1208;O=17;E=2.66;R=6.39;rawP=1.18e-09;adjP=1.22e-07
hsa_GGGCGGR_V$SP1_Q6	23	10424 2119 11069 93035 54102 64093 80758 2066 79191 6117 4122 27123 10265 113452 6786 2983 22920 219699 9423 114826 2118 201176 10590	C=2891;O=23;E=6.37;R=3.61;rawP=5.40e-08;adjP=4.20e-06
hsa_V$CRX_Q4	8	92949 2649 2119 10395 11281 2066 10265 151449	C=266;O=8;E=0.59;R=13.65;rawP=1.44e-07;adjP=8.96e-06
hsa_GATTGGY_V$NFY_Q6_01	13	92949 2119 25841 6425 3664 79191 132204 84900 89797 6786 2118 4703 8292	C=1141;O=13;E=2.51;R=5.17;rawP=1.36e-06;adjP=7.05e-05
hsa_V$OCT1_06	7	5362 3360 2066 79191 115111 138046 339479	C=264;O=7;E=0.58;R=12.04;rawP=2.08e-06;adjP=7.19e-05
hsa_TGACAGNY_V$MEIS1_01	11	6258 4878 5362 64093 25841 89797 115111 3084 22920 1145 10590	C=819;O=11;E=1.80;R=6.10;rawP=1.99e-06;adjP=7.19e-05
hsa_YATTNATC_UNKNOWN	8	11281 10395 79191 339479 8292 4703 117247 151449	C=370;O=8;E=0.82;R=9.82;rawP=1.73e-06;adjP=7.19e-05
hsa_TGGAAA_V$NFAT_Q4_01	16	660 10424 92949 2649 2119 10395 2066 27123 91584 10265 115111 2983 138046 3084 339479 8292	C=1871;O=16;E=4.12;R=3.88;rawP=3.18e-06;adjP=9.89e-05

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).