metabaR

metabaR curates DNA metabarcoding datasets by identifying and filtering artefactual sequences (including reagent contaminants and tag-jumps) and by flagging dysfunctional PCRs to improve data quality for ecological and biodiversity analyses.

Key Features:

• Control-based filtering: Uses experimental negative and positive controls to identify and filter artefactual sequences such as reagent contaminants and tag-jumps.
• PCR replicate assessment: Flags potentially dysfunctional PCR reactions by comparing similarities among PCR replicates.
• Visualization of data characteristics: Provides visualization of data characteristics and distributions within the experimental context to support determination of filtering thresholds.
• Post-bioinformatics curation: Offers a comprehensive suite of curation functions to operate on datasets after initial bioinformatic analyses.
• Pipeline compatibility: Operates on data pre-analysed by various bioinformatic pipelines.
• Marker and platform agnosticism: Applies to any DNA marker or sequencing platform.
• Output compatibility: Generates outputs compatible with downstream analyses using ecological R packages.
• Customizable automated assessment: Includes customizable methods to support automated data quality assessments in DNA metabarcoding studies.

Scientific Applications:

• Biodiversity assessment: Improves accuracy of biodiversity studies across taxa and environmental gradients by removing artefacts from metabarcoding data.
• Environmental research and biomonitoring: Supports environmental research and biomonitoring by reducing sequence artefacts that can lead to misinterpretation.
• Ecological community analyses: Produces curated datasets suitable for downstream ecological analyses using R packages.

Methodology:

Uses experimental negative and positive controls to identify and remove reagent contaminants and tag-jumps, compares PCR replicates to flag dysfunctional reactions, and provides visualizations of data distributions to inform filtering thresholds on datasets generated by prior bioinformatic pipelines.