Global optimal eBURST analysis of multilocus typing data using a graphic matroid approach

BMC Bioinformatics

Table 1 Comparison between eBURST and the proposed implementation.

	# diffs	Group		Ties		Links
Dataset		founder	size	#	breaker	created	deleted
Enterococcus faecium	1	17	268	3	SLV	50–177	50–204
Streptococcus	3	124	78	3	SLV	392–2803	440–2803
pneumoniae		138	189	14	SLV	171–361	338–3163
		217	33	2	SLV	618–3577	1325–1331
Burkholderia	4	48	348	3	SLV	435–667	116–435
pseudomallei		48	348	53	DLV	211–300	56–99
		48	348	3	SLV	70–290	66–67
		48	348	4	DLV	24–643	570–643
Campylobacter	5	21	849	29	SLV	104–492	474–577
jejuni		21	849	14	SLV	353–462	2395–2517
		21	849	2	SLV	2141–2842	1076–2951
		21	849	4	SLV	824–2141	878–2141
		177	53	2	SLV	1022–1503	1387–2162
Neisseria	7	11	296	18	SLV	8–1058	66–1058
spp.		11	296	1	SLV	10–2174	10–5091
		22	344	23	SLV	23–1062	1062–1625
		60	164	9	SLV	1157–1421	1421–1649
		269	322	21	SLV	275–352	352–1163
		1583	67	1	SLV	1905–6717	1579–1901
		1583	67	4	SLV	1590–1928	1599–1903

The following data sets presented no differences: Helicobacter pylori, Streptococcus pyogenes, Staphylococcus aureus, Bacillus cereus, Pseudomonas aeruginosa, Enterococcus faecalis, Klebsiella pneumoniae, Campylobacter upsaliensis, Streptococcus suis, Haemophilus influenzae, Streptococcus uberis, Staphylococcus epidermidis and Streptococcus agalactiae.

ISSN: 1471-2105