# 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 MATTTGCATAWCAAARGM MEME-1 MATTTGCATAWCAAARGM 1.2e-038 1.1e-039 -89.73 0.0 77 193 397 588 0.39896 1.1e-041 96 1 AGTCACCTCATTAGCATAAACTCAGGTGTG MEME-2 AGTCACCTCATTAGCATAAACTCAGGTGTG 6.5e-002 5.9e-003 -5.13 0.0 125 181 26 26 0.69061 6.6e-005 90 1 WTATGCAAATR MEME-3 WTATGCAAATR 1.9e-032 1.7e-033 -75.46 0.0 92 200 365 496 0.46000 1.7e-035 99 2 ATGYWAAT DREME-1 ATGCWAAT 5.2e-017 4.7e-018 -39.89 0.0 99 203 261 360 0.48768 4.7e-020 101 2 TGMATAW DREME-2 TGMATAW 3.1e-029 2.8e-030 -68.05 0.0 90 204 271 362 0.44118 2.8e-032 101 2 KAAAGRA DREME-3 KAAAGRA 9.2e0000 8.3e-001 -0.18 0.0 4 204 10 233 0.01961 1.8e-002 101 2 CATRACA DREME-4 CATRACA 4.8e-016 4.3e-017 -37.68 0.0 90 204 119 149 0.44118 4.3e-019 101 2 ATGCGCAT DREME-7 ATGCGCAT 2.5e-009 2.3e-010 -22.19 0.0 55 203 42 59 0.27094 2.3e-012 101 2 CCTTTSA DREME-8 CCTTTSA 9.3e-002 8.5e-003 -4.77 0.0 102 204 82 121 0.50000 8.4e-005 101 ## # 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).