Amplicon sequencing is a widely used method to characterize microbial communities across environmental and host-associated sample types. However, variation in DNA extraction methods, sequencing batch effects, contamination, and low-quality samples can introduce biases that hinder reproducibility and cross-sample comparisons. Here, we present a modular and reproducible protocol for amplicon sequence cleaning that accommodates diverse sample types and experimental designs. This workflow standardizes quality filtering, contaminant removal, batch correction, and functional annotation to enable robust downstream analyses of bacterial and fungal communities. The protocol integrates the BU16S-ITS pipeline for ASV inference with R-based tools for data cleaning and normalization and is suitable for projects using Illumina sequencing platforms. Code and documentation are available at https: //github. com/k-atherton/AmpliconSequenceDataProcessing.
Atherton et al. (Wed,) studied this question.