# 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 MCMACTRVRCYAHVNRRSC MEME-1 MCMACTRVRCYAHVNRRSC 5.0e-017 3.8e-018 -40.11 0.0 82 372 70 111 0.22043 2.1e-020 185 1 AYGAYCTTCTGATTANNAGTCWGACGCSYT MEME-2 AYGAYCTTCTGATTANNAGTCWGACGCSYT 3.6e-010 2.8e-011 -24.31 0.0 135 361 51 61 0.37396 1.5e-013 180 1 GAWTCGAACCSGGGTYBYMMSGATSRAAAC MEME-3 GAWTCGAACCSGGGTYBYMMSGATSRAAAC 1.8e-003 1.4e-004 -8.88 0.0 151 361 19 20 0.41828 7.7e-007 180 2 AGTGGTWA DREME-1 AGTGGTTA 2.1e-003 1.6e-004 -8.74 0.0 97 383 21 31 0.25326 8.4e-007 191 2 SGGTTCGA DREME-2 SGGTTCGA 1.6e-005 1.2e-006 -13.61 0.0 167 383 78 110 0.43603 6.4e-009 191 2 CAACTKGG DREME-3 CAACTTGG 2.9e-005 2.3e-006 -13.00 0.0 41 383 22 52 0.10705 1.2e-008 191 2 RCGCCTTA DREME-4 GCGCCTTA 2.1e-004 1.6e-005 -11.03 0.0 121 383 43 67 0.31593 8.5e-008 191 2 GCKCTACC DREME-5 GCKCTACC 8.4e0000 6.4e-001 -0.44 0.0 3 383 4 89 0.00783 5.4e-003 191 2 CGWTGCC DREME-6 CGTTGCC 2.0e-001 1.5e-002 -4.18 0.0 120 384 33 58 0.31250 8.1e-005 191 ## # 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).