The evolution, impact and properties of exonic splice enhancers

Table 1 The extent of overlap between each dataset in pairwise combination

Dataset 1	Dataset 2	n 1	n 2	O	E	F	Z	Pvalue
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.

ISSN: 1474-760X