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. 2015 May 1;16:140. doi: 10.1186/s12859-015-0573-5

Table 3.

Comparison of optimal motifs for TFs common to MatBase, Transfac and the union of public databases

ENCODE/funcgen MatBase Transfac Prof. Jaspar vert. Hocomoco HT-Selex SwissRegulon
TF name AUC matrix name AUC matrix name AUC matrix name AUC matrix name AUC matrix name AUC matrix name
ATF3 0.710 V$CREB.02 0.693 M00981 0.694 M00015
Ap2alpha 0.809 V$AP2.02 0.807 M01045 0.816 MA0003.2 0.777 M00004 0.779 selex292 0.754 TFAP2A,C.p2
Ap2gamma 0.799 V$AP2.02 0.765 M00470 0.792 MA0524.1 0.781 M00006 0.784 selex298 0.751 TFAP2A,C.p2
BHLHE40 0.947 V$BHLHB2.01 0.799 M01034 0.885 MA0464.1 0.955 M00022 0.958 selex316 0.917 ARNT_ARNT2_BHLHB2_
MAX_MYC_USF1.p2
CTCF 0.929 V$CTCF.04 0.931 M01259 0.942 MA0139.1 0.940 M00045 0.922 selex2 0.934 CTCF.p2
Cfos 0.751 V$AP1.01 0.759 M00517 0.744 MA0476.1 0.760 M00093 0.742 FOS_FOSB,L1_JUNB,D.p2
Cjun 0.814 V$AP1.01 0.820 M00925 0.799 MA0099.1 0.827 M00183 0.570 JUN.p2
Cmyc 0.700 V$CMYC.01 0.685 M00322 0.702 MA0147.1 0.690 M00216 0.659 ARNT_ARNT2_BHLHB2_
MAX_MYC_USF1.p2
E2F1 0.802 V$E2F3.01 0.764 M00938 0.753 MA0024.2 0.694 M00052 0.723 selex750 0.674 E2F1..5.p2
E2F4 0.682 V$E2F4.01 0.678 M00920 0.689 MA0470.1 0.650 M00055 0.502 selex753 0.654 E2F1..5.p2
E2F6 0.698 V$E2F4.01 0.435 M01252 0.653 MA0471.1 0.681 M00057
EBF 0.740 V$EBF1.01 0.736 M01871 0.721 MA0154.2 0.746 M00037 0.751 selex79 0.692 EBF1.p2
ELF1 0.862 V$ELK1.03 0.835 M02053 0.800 MA0473.1 0.832 M00065 0.836 selex81 0.797 ELF1,2,4.p2
ETS1 0.765 V$ELK3.01 0.753 M02063 0.680 MA0098.1 0.708 M00082 0.765 selex100 0.683 ETS1,2.p2
Egr1 0.831 V$EGR1.01 0.848 M01972 0.822 PB0010.1 0.844 M00060 0.853 selex3 0.841 EGR1..3.p2
FOSL1 0.885 V$AP1.02 0.890 M00517 0.890 MA0477.1 0.865 M00091 0.881 FOS_FOSB,L1_JUNB,D.p2
FOSL2 0.877 V$AP1.01 0.870 M00925 0.865 MA0478.1 0.885 M00092 0.852 FOSL2.p2
FOXA1 0.763 V$FREAC4.01 0.826 M01261 0.832 MA0148.3 0.808 M00094
FOXA2 0.759 V$FREAC4.01 0.735 M02014 0.834 MA0047.2 0.816 M00095 0.834 FOXA2.p3
Gabp 0.873 V$ELK1.03 0.867 M02074 0.879 MA0062.2 0.876 M00116 0.871 selex116 0.870 ELK1,4_GABPA,B1.p3
Gata1 0.711 V$GATA5.01 0.685 M00203 0.683 MA0035.3 0.697 M00117 0.479 GATA1..3.p2
Gata2 0.853 V$GATA2.03 0.834 M00789 0.834 MA0036.2 0.843 M00118 0.538 GATA1..3.p2
HNF4A 0.801 V$HNF4.01 0.838 M02220 0.847 MA0114.2 0.850 M00147 0.837 selex673 0.809 HNF4A_NR2F1,2.p2
HNF4G 0.864 V$HNF4.01 0.811 M00764 0.898 MA0484.1 0.788 M00148
IRF4 0.669 V$ISRE.01 0.641 M00772 0.648 PB0034.1 0.603 M00174 0.665 selex148
Junb 0.912 V$AP1.01 0.912 M00925 0.920 MA0490.1 0.911 M00181 0.900 FOS_FOSB,L1_JUNB,D.p2
Jund 0.820 V$AP1.01 0.823 M00925 0.817 MA0491.1 0.827 M00182 0.805 FOS_FOSB,L1_JUNB,D.p2
MEF2A 0.643 V$MEF2.02 0.650 M00231 0.653 MA0052.2 0.616 M00204 0.615 selex156 0.604 MEF2A,B,C,D.p2
MEF2C 0.721 V$MEF2.02 0.682 M00941 0.719 MA0497.1 0.664 M00205 0.669 MEF2A,B,C,D.p2
Max 0.738 V$CMYC.01 0.703 M00322 0.700 PB0043.1 0.720 M00199 0.730 selex326 0.711 ARNT_ARNT2_BHLHB2_
MAX_MYC_USF1.p2
NFKB 0.896 V$NFKAPPAB65.02 0.891 M00774 0.878 MA0105.3 0.872 M00235 0.776 selex189 0.861 NFKB1_REL_RELA.p2
NR4A1 0.512 V$NBRE.01 0.492 M01217 0.542 M00259
Nanog 0.560 V$HOXA2.01 0.631 M01247 0.556 M00221 0.630 NANOGmouse.p2
Nfe2 0.855 V$NFE2.01 0.846 M00037 0.877 MA0501.1 0.882 M00231 0.771 selex392 0.835 NFE2.p2
Nrf1 0.951 V$NRF1.01 0.969 M00652 0.963 MA0506.1 0.973 M00264 0.977 selex194 0.968 NRF1.p2
Nrsf 0.838 V$NRSF.02 0.879 M01256 0.850 MA0138.2 0.854 M00316 0.847 REST.p3
POU2F2 0.513 V$OCT1.02 0.498 M00210 0.481 MA0507.1 0.504 M00290 0.503 selex232 0.503 POU2F1..3.p2
POU5F1 0.868 V$OCT3_4.02 0.857 M01125 0.881 MA0142.1 0.874 M00294 0.857 POU5F1_SOX2dimer.p2
PU1 0.932 V$SPI1.05 0.884 M01203 0.914 MA0080.3 0.922 M00350 0.860 selex123 0.884 SPI1.p2
Pax5 0.613 V$PAX5.01 0.613 M00143 0.713 MA0014.2 0.729 M00274 0.768 selex200 0.606 PAX5.p2
Pbx3 0.739 V$PBX1_MEIS1.01 0.546 M00998 0.758 M00280
RXRA 0.714 V$PPARG.03 0.608 M02272 0.707 MA0065.1 0.693 M00326 0.731 selex710 0.720 RXRG_dimer.p3
SP1 0.559 V$SP1.03 0.552 M00932 0.561 MA0079.3 0.555 M00346 0.547 selex29 0.551 SP1.p2
SP2 0.711 V$SP4.01 0.719 M01783 0.726 MA0516.1 0.676 M00347
Srf 0.681 V$SRF.05 0.693 M00186 0.661 MA0083.1 0.657 M00355 0.657 selex159 0.656 SRF.p3
Tcf12 0.723 V$ASCL2.01 0.679 M00698 0.712 MA0521.1 0.703 M00152 0.574 TAL1_TCF3,4,12.p2
Tr4 0.601 V$HNF4.01 0.644 M01776 0.652 MA0504.1 0.623 M00256 0.611 selex676
USF1 0.947 V$USF1.02 0.936 M00121 0.903 MA0093.2 0.945 M00396 0.935 selex352 0.932 ARNT_ARNT2_BHLHB2_
MAX_MYC_USF1.p2
Yy1 0.778 V$YY1.03 0.723 M02044 0.713 MA0095.2 0.735 M00394 0.756 selex33 0.657 YY1.p2
ZBTB33 0.489 V$KAISO.01 0.517 M01119 0.881 MA0527.1 0.749 M00184
ZBTB7A 0.699 V$ZF9.01 0.682 M01100 0.640 M00404 0.632 selex37
ZEB1 0.766 V$ZEB1.01 0.689 M00414 0.752 MA0103.2 0.686 M00409 0.734 ZEB1.p2
Znf263 0.685 V$ZNF263.01 0.762 M01587 0.653 MA0528.1

For each TF the motif with the highest AUC from each database is presented. The best motifs from all databases and the corresponding AUC are bolded (note that for FOXA2 motifs from Jaspar and SwissRegulon are both optimal). AUC are calculated with respect to negative sequences composed of flanks of ChIP-seq peaks.