eDNA Metabarcoding Usage Guide

eDNA Metabarcoding Usage Guide

Overview

Environmental DNA (eDNA) metabarcoding identifies species from trace DNA shed into water, soil, or air. This skill covers the full workflow from raw amplicon reads to species occurrence tables: primer removal, quality filtering, denoising (OBITools3 or DADA2), taxonomy assignment against curated reference databases (MIDORI2, MitoFish, BOLD), contamination filtering with decontam, and occupancy modeling for detection probability correction.

Prerequisites

• OBITools3 (pip install OBITools3)
• cutadapt (pip install cutadapt)
• R with DADA2 (BiocManager::install('dada2'))
• decontam (BiocManager::install('decontam'))
• microDecon (remotes::install_github('donaldtmcknight/microDecon'))
• occumb (install.packages('occumb')) and JAGS for occupancy modeling
• Reference database formatted for the target marker (MIDORI2, MitoFish, BOLD)

Quick Start

Tell your AI agent what you want to do:

• "Process my eDNA water samples to identify fish species using 12S MiFish primers"
• "Run the OBITools3 pipeline on my COI metabarcoding data"
• "Denoise my eDNA amplicon reads with DADA2 and assign taxonomy against MIDORI2"
• "Filter contamination from my eDNA dataset using extraction blanks"
• "Run occupancy modeling on my replicated eDNA samples to correct for detection probability"

Example Prompts

Basic Processing

"I have paired-end FASTQ files from eDNA water samples amplified with MiFish 12S primers. Remove primers with cutadapt, denoise with DADA2, and assign taxonomy against MitoFish."

"Run the full OBITools3 pipeline on my COI metabarcoding data: align paired ends, dereplicate, denoise, and assign taxonomy."

Contamination Control

"I have 48 eDNA samples and 6 extraction blanks. Use decontam to identify and remove contaminant ASVs using both frequency and prevalence methods."

"My eDNA dataset has tag-jumping artifacts between samples. Use microDecon to clean up the cross-contamination."

Occupancy Modeling

"I collected 3 eDNA replicates per site across 20 sites. Fit an occupancy model with occumb to estimate true species occurrence probabilities."

Database Preparation

"Download and format the MIDORI2 COI database for DADA2 taxonomy assignment."

What the Agent Will Do

1. Remove primer sequences with cutadapt using linked adapter mode for the target barcode region
2. Process reads through either OBITools3 (dereplication + denoising) or DADA2 (ASV inference)
3. Filter sequences by length and quality appropriate for the target marker
4. Remove chimeric sequences and PCR/sequencing artifacts
5. Assign taxonomy against the appropriate reference database with confidence thresholds
6. Filter contamination using negative controls (decontam) and tag-jumping correction (microDecon)
7. Optionally fit occupancy models to estimate detection-corrected species occurrence
8. Export a species-by-site occurrence or abundance table

Tips

• Always include extraction blanks and PCR negative controls in sequencing runs for decontam filtering
• COI has a wider barcode gap than 12S, making species-level assignment more reliable for invertebrates
• MiFish 12S is preferred for fish eDNA due to shorter amplicon and universal primer performance
• DADA2 produces exact ASVs (single-nucleotide resolution) while OBITools3 clusters at a similarity threshold
• For rare species detection, aim for at least 50,000 reads per sample after filtering
• Biological replicates (separate water collections) are more informative than PCR replicates for occupancy modeling
• Always check chimera rates: above 20% suggests issues with PCR conditions or primer dimers
• The MIDORI2 database is updated regularly; always use the latest version for best taxonomy coverage

Related Skills

• biodiversity-metrics - Diversity analysis from species occurrence tables
• community-ecology - Environmental gradient analysis of communities
• microbiome/amplicon-processing - 16S clinical microbiome alternative
• read-qc/quality-reports - Upstream read quality assessment