I’m analyzing samples derived from mouse stool. This is my first time using qiime. I have imported my pre-demultiplexed paired-end fastq files and run dada2 denoising on them. From the overview page (https://docs.qiime2.org/2019.7/tutorials/overview/#clustering), it states that clustering must be preceded by quality filtering and dereplication and followed by chimera and OTU filtering. The flowcharts show dereplication as producing a FeatureTable[Frequency], which is also the output from dada2, and the Demultiplexing flowchart shows data flowing through dada2 denoising OR through quality and dereplication modules. My understanding is that dada2 does quality and chimera filtering, so is dada2 denoising an alternative to OTU clustering, or are the filtering steps not required before OTU clustering if dada2 is used? Does dada2 do dereplication as well? If I’ve run the denoising, can I directly run OTU clustering on the output?