# 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 CYTGGCACVRTGCCAR MEME-1 CYTGGCACVRTGCCAR 2.8e-044 3.9e-047 -106.87 0.0 99 485 115 150 0.20412 1.6e-049 242 1 BTKTBTKTGTKTRTKTBTKTGTKTKKB MEME-2 BTKTBTKTGTKTRTKTBTKTGTKTKKB 9.1e-005 1.2e-007 -15.91 0.0 96 474 135 405 0.20253 5.2e-010 236 1 CACATCCTBHAGTARCTTT MEME-3 CACATCCTBHAGTARCTTT 5.2e-013 7.0e-016 -34.89 0.0 104 482 52 76 0.21577 2.9e-018 240 2 CTTGGCWC DREME-1 CTTGGCWC 1.8e-007 2.5e-010 -22.13 0.0 77 493 44 92 0.15619 1.0e-012 246 2 CYTGGCA DREME-2 CCTGGCA 5.3e-014 7.2e-017 -37.17 0.0 56 494 60 151 0.11336 2.9e-019 246 3 M1970_1.02 NFIC TGCCAA 2.4e-004 3.3e-007 -14.92 0.0 55 495 115 588 0.11111 1.3e-009 247 3 M5660_1.02 NFIA TTGGCANNDTGCCAR 3.2e-022 4.3e-025 -56.10 0.0 64 486 114 296 0.13169 1.8e-027 242 3 M5662_1.02 NFIB TTGGCAHNDTGCCAR 7.7e-023 1.0e-025 -57.52 0.0 64 486 115 296 0.13169 4.3e-028 242 3 M5664_1.02 NFIX TTGGCANNNNGCCAR 7.8e-016 1.1e-018 -41.40 0.0 66 486 134 427 0.13580 4.3e-021 242 3 M6247_1.02 FOXO4 MRTAAACAA 9.3e0000 1.3e-002 -4.37 0.0 48 492 81 532 0.09756 5.2e-005 245 ## # 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).