Comparison to Mothur + Consension
We randomly selected five out of the 61 fungi datasets from Wurzbacher et al., (2019), ranging from 201 to 447 reads per dataset (Supplementary Table 1). These cover five fungi species of the genus Inocybe for ribosomal DNA (rDNA) and the full ribosomal tandem repeat region (TR). We provide alignments of the corresponding Sanger sequences with our consensus sequences in the Supplementary (Supplementary files 2-6). In their approach, Wurzbacher et al., (2019) first perform operational taxonomic unit (OTU) clustering on the read data using Mothur (Schloss et al., 2009). Next, they create consensus sequences using Consension (Wurzbacher et al., 2019).
In general, we see that for both ONT and PacBio data NGSpeciesID and the Mothur + Consension pipeline perform equally well, generating consensus sequences with 98.6% to 100% accuracy (Table 1). In three out of the five cases, the two pipelines produced consensus sequences with the same accuracy, while in one case each software slightly outperformed the other (Table 1). Medaka polishing outperformed Racon polishing in four out of five cases (Table 1).