# WARNING: this file is not sorted!
# db id alt 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 neg_sites_in_bin neg_sites neg_adj_pvalue log_neg_adj_pvalue fisher_adj_pvalue log_fisher_adj_pvalue
1 MA0090.2 TEAD1 7.7e-022 1.5e-024 -54.87 0.0 135 491 196 359 0.27495 6.1e-027 245 32 153 1.0e0000 0.00 4.3e-010 -21.56
1 MA0139.1 CTCF 2.4e0000 4.6e-003 -5.39 0.0 144 482 73 160 0.29876 1.9e-005 240 13 52 1.0e0000 0.00 7.6e-001 -0.27
1 MA0599.1 KLF5 5.5e0000 1.1e-002 -4.55 0.0 453 491 296 303 0.92261 4.3e-005 245 92 99 1.0e0000 0.00 1.0e0000 -0.00
1 MA0808.1 TEAD3 2.2e-036 4.2e-039 -88.37 0.0 135 493 194 299 0.27383 1.7e-041 246 24 97 1.0e0000 0.00 8.5e-010 -20.88
1 MA0809.1 TEAD4 3.5e-025 6.7e-028 -62.57 0.0 135 491 200 353 0.27495 2.7e-030 245 32 152 1.0e0000 0.00 1.1e-011 -25.23
##
# 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.
# 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).
# neg_sites_in_bin: The number of negative sequences where the best
# match to the motif falls in the reported region.
# This value is rounded but the underlying value may contain
# fractional counts.
# Note: This number may be less than the number of negative 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.
# neg_sites: The number of negative sequences containing a match to the
# motif above the minimum score threshold.
# When score optimization is enabled the score threshold may be raised
# higher than the minimum.
# neg_adj_pvalue: The probability that any tested region in the negative
# sequences would be as enriched for best matches to this motif
# according to the Binomial test.
# log_neg_adj_pvalue: Log of negative adjusted p-value.
# fisher_adj_pvalue: Fisher adjusted p-value before it gets adjusted to the
# number of motifs in the input database(s).
# Refers to the E-value definition using the discriminative mode.
# log_fisher_adj_pvalue: Log of Fisher adjusted p-value.