Table 1

The extent of overlap between each dataset in pairwise combination
Dataset 1 Dataset 2 n 1 n 2 O E F Z P value
RESCUE PESE 238 238 75 13.8 5.42 17.3 < 0.001
RESCUE ESR 238 285 55 16.6 3.32 10.1 < 0.001
RESCUE Ke-ESE400 238 400 54 23.2 2.32 6.8 < 0.001
PESE ESR 238 285 48 16.6 2.90 8.9 < 0.001
PESE Ke-ESE400 238 400 65 23.2 2.80 9.2 < 0.001
ESR Ke-ESE400 285 400 33 27.8 1.19 1.0 0.12195
RESCUE Ke-ESE 238 1182 125 68.7 1.82 8.2 <0.001
PESE Ke-ESE 238 1182 137 68.7 1.99 9.9 <0.001
ESR Ke-ESE 285 1182 98 82.2 1.19 2.1 0.015

n1 = number of motifs in dataset 1; n2 = number of motifs in dataset 2; O = number of motifs in common between dataset 1 and dataset 2; E = expected = (n1 * n2)/T; where T is the total number of possible hexamers, that is, 4,096; F = overlap factor = O/E; factor >1 indicates more overlap than expected of two independent groups. Z score is the difference between O and E normalised by the standard deviation (derived from simulation). P values in bold are those significant after Bonferonni correction assuming P <0.05/9.

Cáceres and Hurst

Cáceres and Hurst Genome Biology 2013 14:R143   doi:10.1186/gb-2013-14-12-r143

Open Data