Demulticoder: An R Package for the Simultaneous Analysis of Multiplexed Metabarcodes

Area of Science:

• Ecology
• Bioinformatics
• Molecular Biology

Background:

• Metabarcoding uses DNA sequences to identify organisms in communities.
• Existing workflows are inefficient for multiple or novel metabarcodes, especially for diverse taxa like soil microbes.
• Analyzing diverse taxa often requires multiple metabarcodes, increasing workflow complexity.

Purpose of the Study:

• To develop demulticoder, an R package automating DADA2 analysis for multiple metabarcodes.
• To streamline metabarcoding data processing, reducing manual input and enabling automated analysis of multiplexed data.
• To provide a versatile tool for analyzing single, multiplexed, or pooled metabarcodes.

Main Methods:

• Developed the demulticoder R package for automated metabarcoding analysis.
• Integrated DADA2 for sequence variant identification.
• Updated the oomycete rps10 barcode database with revised taxonomic information.
• Compared demulticoder to a standard workflow using a multiplexed ITS1 and rps10 dataset.

Main Results:

• Demulticoder reduced manual input steps from 28 to 4 compared to standard workflows.
• Data quality and downstream analysis results (exploratory, diversity, differential abundance) were comparable.
• The oomycete rps10 database was updated for improved taxonomic accuracy.
• Demulticoder successfully analyzed multiplexed ITS1 and rps10 metabarcodes.

Conclusions:

• Demulticoder simplifies and automates multi-metabarcoding data analysis.
• The package offers a versatile, efficient, and user-friendly alternative to standard workflows.
• Demulticoder ensures high data quality and is suitable for diverse metabarcoding applications.