I have recently been tasked with analyzing a heterogeneous microbial sample composed of 16S data generated on a MinION sequencer, with the goal of assigning taxonomies and calculating respective abundance.
It is my understanding that traditional preprocessing methods such as Dada2, Unoise3, and Deblur would likely not be appropriate for this kind of data given the poorer read quality inherent with nanopore sequencing. To give an example, the average read quality of this current experiment is a Phred score of 15 and an average read length of 1500bp.
Furthermore, it would seem best to try and utilize a classifier that makes use of a full length 16S reference, rather than just the V3 region, to try and offset the higher error rate. But are there any classifiers that do this out of the box?
I am very interested to hear of any advice or input the community has on this. Thanks!