GenFamClust: an accurate, synteny-aware and reliable homology inference algorithm

Table 4 Similarity and statistical dependence between homology inference methods. Mutual information scores are found above the diagonal and Jaccard similarity coefficient are found below the diagonal

Mutual information/		GenFamClust			Neighborhood correlation			SiLiX	MCL	hcluster_sg
Jaccard coefficient		Aver	Comp	Sing	Aver	Comp	Sing
GFC	Average		0.146	0.628	0.139	0.145	0.517	0.149	0.167	0.159
	Complete	0.599		0.604	0.123	0.094	0.497	0.112	0.158	0.125
	Single	0.117	0.071		0.618	0.605	0.785	0.581	0.631	0.613
NC	Average	0.815	0.725	0.096		0.121	0.508	0.130	0.164	0.143
	Complete	0.621	0.925	0.073	0.758		0.498	0.113	0.158	0.125
	Single	0.169	0.103	0.573	0.138	0.106		0.477	0.518	0.505
SiLiX		0.273	0.339	0.037	0.320	0.345	0.053		0.154	0.126
MCL		0.733	0.520	0.122	0.647	0.537	0.176	0.261		0.173
hcluster_sg		0.586	0.646	0.083	0.623	0.658	0.119	0.277	0.496

The eight highest values for Jacquard’s similarity coefficient (below the diagonal) and mutual information (above the diagonal) are bold-faced to show the pair of software with most similarity and statistical dependence

ISSN: 2730-7182