# 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 GTGTGTGTGTGTGTGTGTGTGT MEME-1 GTGTGTGTGTGTGTGTGTGTGT 1.7e-009 2.3e-012 -26.81 0.0 171 479 100 150 0.35699 9.5e-015 239 1 GWGTGDGTGWGKGWGWGDRTGA MEME-2 GWGTGDGTGWGKGWGWGDRTGA 2.1e-005 2.9e-008 -17.37 0.0 109 479 157 431 0.22756 1.2e-010 239 1 RRRRGCCTTGAATGCCAAGCYMAGGA MEME-3 RRRRGCCTTGAATGCCAAGCYMAGGA 3.3e-013 4.4e-016 -35.35 0.0 101 475 47 65 0.21263 1.9e-018 237 2 ATTCRAGG DREME-1 ATTCAAGG 5.9e-005 8.0e-008 -16.34 0.0 93 493 57 133 0.18864 3.3e-010 246 3 M5425_1.02 ETV6 CCGGAASCGGAAGYR 1.0e0001 1.3e-002 -4.31 0.0 160 486 163 384 0.32922 5.6e-005 242 3 M5981_1.02 ZSCAN4 TTTTCAGKGTGTGCA 2.9e-003 4.0e-006 -12.44 0.0 172 486 149 290 0.35391 1.6e-008 242 3 M6200_1.02 EGR3 WGAGTGGGYGT 5.8e0000 7.8e-003 -4.85 0.0 150 490 210 541 0.30612 3.2e-005 244 3 M6212_1.02 EPAS1 CMCACGYAYDCAC 8.4e0000 1.1e-002 -4.48 0.0 112 488 164 539 0.22951 4.7e-005 243 ## # 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).