Choice of assembly software has a critical impact on virome characterisation

Microbiome

Table 3 The number of false positive and false negative contigs generated by each assembler for (a) mock community A and (b) mock community B along with the sensitivity rates for each

	False positives	False negative	True positive	No. of contigs returned^a	Sensitivity
A
ABySS (k-mer 63)	52	4	8	61	66.67
ABySS (k-mer 127)	50	6	6	56	50.00
CLC	1143	0	12	1299	100.00
Geneious	53	0	12	65	100.00
IDBA UD	0	0	12	12	100.00
MEGAHIT	0	0	12	13	100.00
MetaVelvet	0	3	9	26	75.00
MIRA	0	0	12	89	100.00
Ray Meta	0	0	12	12	100.00
SOAPdenovo2	2	0	12	23	100.00
SPAdes	0	0	12	14	100.00
SPAdes meta	0	0	12	14	100.00
SPAdes sc	1513	0	12	1527	100.00
SPAdes sc careful	0	0	12	15	100.00
Velvet	0	3	9	26	75.00
VICUNA	4969	0	12	5385	100.00
B
ABySS (k-mer 63)	60	4	8	69	66.67
ABySS (k-mer 127)	132	6	6	139	50.00
CLC	450	0	12	505	100.00
Geneious	14	0	12	30	100.00
IDBA UD	0	0	12	12	100.00
MEGAHIT	0	0	12	14	100.00
MetaVelvet	0	1	11	24	91.67
MIRA	94	1	11	157	91.67
Ray Meta	0	0	12	13	100.00
SOAPdenovo2	2	2	10	27	83.33
SPAdes	0	0	12	13	100.00
SPAdes meta	0	0	12	14	100.00
SPAdes sc	593	0	12	607	100.00
SPAdes sc careful	0	0	12	14	100.00
Velvet	0	1	11	24	91.67
VICUNA	0	0	12	15	100.00

ISSN: 2049-2618