# WARNING: this file is not sorted! # db id alt consensus E-value adj_p-value log_adj_p-value bin_location bin_width total_width sites_in_bin total_sites p_success p-value mult_tests 1 RSHGGGCGSHGS MEME-1 RSHGGGCGSHGS 3.1e-036 4.2e-039 -88.36 0.0 95 489 261 599 0.19427 1.7e-041 244 2 HGGGCGY DREME-1 HGGGCGC 5.2e-040 7.0e-043 -97.07 0.0 132 494 292 521 0.26721 2.8e-045 246 2 MGCCCR DREME-2 MGCCCR 1.6e-013 2.2e-016 -36.05 0.0 143 495 270 586 0.28889 8.9e-019 247 2 GTGCCCK DREME-3 GTGCCCK 3.8e-010 5.1e-013 -28.31 0.0 124 494 106 208 0.25101 2.1e-015 246 2 AGGCGY DREME-4 AGGCGC 9.9e-002 1.3e-004 -8.92 0.0 165 495 192 428 0.33333 5.4e-007 247 3 M0212_1.02 (TCFL5)_(Mus_musculus)_(DBD_1.00) NBCDCGHGVN 9.2e0000 1.2e-002 -4.38 0.0 411 491 432 480 0.83707 5.1e-005 245 3 M0443_1.02 (KLF12)_(Mus_musculus)_(DBD_1.00) DGGGCGKGGY 1.7e0000 2.3e-003 -6.08 0.0 395 491 521 598 0.80448 9.4e-006 245 3 M4536_1.02 E2F1 VRRVRGVGCGCGCRS 3.5e-003 4.8e-006 -12.25 0.0 124 486 211 589 0.25514 2.0e-008 242 3 M4612_1.02 CTCFL CCRSCAGGGGGCGCY 7.7e-004 1.0e-006 -13.78 0.0 152 486 239 556 0.31276 4.3e-009 242 3 M5512_1.02 HIC2 VSYGGGCAY 1.4e-001 1.8e-004 -8.61 0.0 70 492 127 586 0.14228 7.5e-007 245 ## # Detailed descriptions of columns in this file: # # db: The name of the database (file name) that contains the motif. # id: A name for the motif that is unique in the motif database file. # alt: An alternate name of the motif that may be provided # in the motif database file. # consensus: A consensus sequence computed from the motif. # E-value: The expected number motifs that would have least one. # region as enriched for best matches to the motif as the reported region. # The E-value is the p-value multiplied by the number of motifs in the # input database(s). # adj_p-value: The probability that any tested region would be as enriched for # best matches to this motif as the reported region is. # By default the p-value is calculated by using the one-tailed binomial # test on the number of sequences with a match to the motif # that have their best match in the reported region, corrected for # the number of regions and score thresholds tested. # The test assumes that the probability that the best match in a sequence # falls in the region is the region width divided by the # number of places a motif # can align in the sequence (sequence length minus motif width plus 1). # When CentriMo is run in discriminative mode with a negative # set of sequences, the p-value of a region is calculated # using the Fisher exact test on the # enrichment of best matches in the positive sequences relative # to the negative sequences, corrected # for the number of regions and score thresholds tested. # The test assumes that the probability that the best match (if any) # falls into a given region # is the same for all positive and negative sequences. # log_adj_p-value: Log of adjusted p-value. # bin_location: Location of the center of the most enriched region. # bin_width: The width (in sequence positions) of the most enriched region. # A best match to the motif is counted as being in the region if the # center of the motif falls in the region. # total_width: The window maximal size which can be reached for this motif: # rounded(sequence length - motif length +1)/2 # sites_in_bin: The number of (positive) sequences whose best match to the motif # falls in the reported region. # Note: This number may be less than the number of # (positive) sequences that have a best match in the region. # The reason for this is that a sequence may have many matches that score # equally best. # If n matches have the best score in a sequence, 1/n is added to the # appropriate bin for each match. # total_sites: The number of sequences containing a match to the motif # above the score threshold. # p_success: The probability of falling in the enriched window: # bin width / total width # p-value: The uncorrected p-value before it gets adjusted to the # number of multiple tests to give the adjusted p-value. # mult_tests: This is the number of multiple tests (n) done for this motif. # It was used to correct the original p-value of a region for # multiple tests using the formula: # p' = 1 - (1-p)^n where p is the uncorrected p-value. # The number of multiple tests is the number of regions # considered times the number of score thresholds considered. # It depends on the motif length, sequence length, and the type of # optimizations being done (central enrichment, local enrichment, # score optimization).