| | n. ESVs (*) | n. MOTUs | Single-ESV MOTUs | ESVs/MOTU (*) | Reads/MOTU |
|---|
Original | 330,382 | – | – | – | – |
Du (**) | 60,198 | – | – | – | – |
Da | 32,798 | – | – | – | – |
Du_e (***) | 113,133 | – | – | – | – |
S | 330,382 | 19,012 | 12,257 | 17.378 | 511.194 |
Du_S | 60,198 | 19,058 | 12,471 | 3.159 | 509.961 |
S_Du | 75,069 | 19,012 | 12,433 | 3.949 | 511.194 |
Da_S | 32,798 | 19,167 | 15,565 | 1.711 | 507.060 |
S_Da | 35,376 | 19,012 | 15,198 | 1.861 | 511.194 |
Du_d_S | 60,198 | 19,058 | 12,471 | 3.159 | 509.960 |
Du_c_S | 60,198 | 19,058 | 12,471 | 3.159 | 509.960 |
Du_e_S | 113,133 | 19,016 | 12,365 | 5.949 | 511.087 |
Du_e_d_S | 113,133 | 19,016 | 12,365 | 5.949 | 511.087 |
Du_e_c_S | 113,133 | 19,016 | 12,365 | 5.949 | 511.087 |
- All datasets had 9,718,827 reads. 1-ESV MOTUs refer to the number of MOTUs with just one ESV. Codes of the datasets: Du, denoised with UNOISE3 algorithm (unless otherwise stated, it refers to the original formulation giving precedence to abundance ratio); Da, denoised with DADA2 algorithm; S, clustered with SWARM algorithm; Du_S, denoised (UNOISE3) and clustered; S_Du, clustered and denoised (UNOISE3); Da_S, denoised (DADA2) and clustered; S_Da, clustered and denoised (DADA2); Du_d_S, denoised (UNOISE3) with precedence to distance and clustered; Du_c_S, denoised (UNOISE3) with combined precedence and clustered; Du_e _S, denoised (UNOISE3) with correction taking into account the entropy of the codon positions and clustered; Du_e_d_S, denoised (UNOISE3) with correction plus precedence to distance and clustered; Du_e_c_S, denoised (UNOISE3) with correction plus combined precedence and clustered
- *For the original and S datasets the number of sequences instead of ESVs is used
- **The same values apply to Du_d (distance precedence) and Du_c (combined precedence)
- ***The same values apply to Du_e_d (distance precedence) and Du_e_c (combined precedence)
