Table 3.

OTUs produced after treating the data with different noise removal approaches

	Qualitative							Quantitative
Approaches	Total OTUs	Correclt OTUs	Over-splitted OTUs	Missed OTUs	Noisy	Contaminants	Others	Approaches	Rare-OTUs	Redundant OTUs
NoDe	22	17	4	0	1	0	0	NoDe	4	18
AmpliconNoise	29	16	4	1	2	1	5	AmpliconNoise	11	18
Denoiser	24	16	3	1	1	0	4	Denosier	7	17
Pre-cluster	46	17	24	0	4	0	0	Pre-cluster	22	24
Acacia	46	17	23	0	5	1	0	Acacia	21	25
Non denoised	58	17	29	0	5	1	7	Non Denoised	35	17

The left side of the table displays the qualitative OTU assessment and the right side displays the quantitative analysis. For the qualitative analysis, we counted the number of “correct OTUs” (classified as one of the mock species), “noisy OTUs” (classified as one of mock species but only classified until Class, Order or Family level), “missed OTUs” (number of undetected mock species), “over-splitted OTUs” (correct yet redundant classification), “contaminant OTUs” (classified as species no belonging to mock) and “other OTUs” (OTUs unclassified at the Class level or higher). In the quantitative analysis, the number of OTUs with a redundancy below 0.1% (rare OTUs) and the ones with a redundancy above 0.1% (Redundant OTUs) were counted.