# 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 BDTGGYBYAGTGGKTARVGSS MEME-2 BDTGGYBYAGTGGKTARVGSS 3.1e-002 2.0e-003 -6.24 0.0 74 390 28 66 0.18974 1.0e-005 194 1 RRTGTAYGGRTGTWW MEME-3 RRTGTAYGGRTGTWW 6.2e0000 3.9e-001 -0.95 0.0 74 396 31 101 0.18687 2.5e-003 197 2 GGTASC DREME-5 GGTAGC 2.6e0000 1.6e-001 -1.82 0.0 93 405 31 79 0.22963 8.7e-004 202 2 ACTYGGCC DREME-6 ACTYGGCC 8.4e0000 5.2e-001 -0.65 0.0 163 403 50 90 0.40447 3.7e-003 201 2 GTGATAR DREME-7 GTGATAG 8.8e0000 5.5e-001 -0.59 0.0 200 404 23 30 0.49505 4.0e-003 201 2 CABACGC DREME-10 CABACGC 8.5e0000 5.3e-001 -0.63 0.0 172 404 16 21 0.42574 3.8e-003 201 2 CACTATAK DREME-11 CACTATAT 1.6e0000 1.0e-001 -2.29 0.0 215 403 12 12 0.53350 5.3e-004 201 2 CAAAGCAY DREME-12 CAAAGCAY 7.0e0000 4.4e-001 -0.83 0.0 267 403 75 94 0.66253 2.9e-003 201 ## # 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).