RAPID: an interactive R/Shiny platform for end-to-end 16S rRNA and ITS amplicon sequence analysis using DADA2

Abstract Motivation Amplicon sequencing of 16S rRNA and internal transcribed spacer (ITS) gene regions is the most widely used approach for characterizing bacterial and fungal communities. The DADA2 pipeline has become the standard for inferring amplicon sequence variants (ASVs), offering single-nucleotide resolution over traditional OTU clustering. However, executing the full DADA2 workflow requires R programming proficiency and manual coordination of multiple sequential steps, presenting a substantial barrier for researchers in clinical, environmental, and agricultural sciences who lack computational training. Results We present RAPID (R-based Amplicon Pipeline for Interactive DADA2), a pair of R/Shiny applications providing complete graphical user interfaces for 16S rRNA and ITS amplicon analysis. The 16S application implements a 10-step guided workflow from raw paired-end FASTQ files through quality filtering, denoising, paired-read merging, chimera removal, SILVA-based taxonomy assignment, phyloseq construction with data transformation (rarefaction, relative abundance, or CLR), visualization (rarefaction curves, alpha diversity, NMDS, PCoA, abundance), PERMANOVA, and ANCOM-BC2 differential abundance analysis. The ITS application extends this to 11 steps, adding automated primer removal via cutadapt with support for multiple primers and length-variable amplicons, and uses the UNITE database for fungal taxonomy. Both applications feature asynchronous background processing, session persistence, real-time progress monitoring, publication-ready figure export at 300 DPI, and comprehensive CSV/PNG result downloads. Availability Raw 16S rRNA amplicon sequences are available in the NCBI Sequence Read Archive under BioProject accession PRJNA1499817. RAPID is freely available at https://github.com/beantkapoor786/RAPID and archived at 10.5281/zenodo.21628564. Both applications can be installed locally on any system with R (≥4.0) and run as local web applications. Supplementary information Supplementary data are available at Bioinformatics online.