Sequence Processing
We processed raw sequence data with the Quantitative Insights Into
Microbial Ecology (QIIME2 version 2019.1) pipeline (Caporaso et
al. 2010; Bolyen et al. 2019). In QIIME2, following standard
demultiplexing and quality filtering, we generated amplicon sequence
variants (ASVs) using the Divisive Amplicon Denoising Algorithm (DADA2)
(Callahan et al. 2016). DADA2 statistically infers sample
sequences and implements quality control elements including exclusion of
singletons, chimera removal, and sequence error elimination. We trimmed
all sequences outside base pair positions 13 and 145 base pairs to
remove the primers. We classified ASV taxonomies using the Silva
reference database (Quast et al. 2012, version 132). We
identified bacterial contaminants using a frequency-based algorithm in
the R package Decontam (Davis et al. 2018). We removed
contaminants and negative controls from subsequent analyses.