omicverse-microbiome-16s-amplicon-dada2

You can process raw 16S amplicon paired-end FASTQs into an analyzed AnnData object by running an end-to-end pipeline that handles filtering, ASV inference, chimera removal, SINTAX taxonomy assignment, and count-table construction.

The best way to run DADA2 and vsearch for microbiome diversity analysis is using a unified workflow that computes rarefaction-aware alpha and beta diversity, ordination, and differential abundance directly on the inferred ASV count table.

SINTAX taxonomy annotation works with ASV count tables by assigning taxonomic classifications to inferred sequences, which are then integrated into an AnnData object alongside sample metadata for downstream ordination and differential abundance analysis.

Yes, validated sample metadata is required to perform 16S amplicon differential abundance analysis, as it provides the necessary group assignments for computing Wilcoxon differential abundance and rarefaction-aware diversity statistics.

Yes, you can inspect individual pipeline stages after denoising 16S reads with DADA2, as the workflow supports stepwise inspection to validate or replace specific stages like filtering, chimera removal, or taxonomy assignment.

Your 16S amplicon workflow requires a SINTAX reference database to accurately assign taxonomy to inferred ASV sequences, ensuring the resulting AnnData object contains valid taxonomic classifications for downstream microbiome analytics.