FACEPAI

FACEPAI processes environmental DNA (eDNA) high-throughput sequencing barcode data to assign sequences to known taxa using reference databases for ecological and taxonomic research.


Key Features:

  • Efficiency: Processes high-throughput barcode sequence datasets in under 15 minutes depending on sequence volume.
  • Low memory footprint: Operates with memory usage below 2 GB on standard desktop PCs.
  • Automation: Automates sequence filtering, clustering, and taxonomic identification to produce repeatable results.
  • Reference database formatting: Requires formatting of reference databases using the CaPReSe script.
  • Open-source integration: Integrates several open-source applications for processing and identification.

Scientific Applications:

  • Environmental surveys: Applies to eDNA datasets from soil, water, sediment, trap alcohol, and bulk samples for environmental surveys.
  • Taxonomic research: Supports taxonomic assignment and barcode-based identification for taxonomic studies.
  • Biodiversity assessments: Facilitates rapid biodiversity assessments from large sequencing datasets.
  • Species distribution modeling: Provides occurrence data useful for species distribution modeling.
  • Ecosystem monitoring: Enables monitoring of ecosystem changes over time via repeatable eDNA analyses.

Methodology:

Reference databases are formatted with the CaPReSe script; the pipeline then automates filtering, clustering, and taxonomic identification and can process multiple samples in succession while integrating several open-source applications.

Topics

Details

License:
GPL-3.0
Tool Type:
command-line tool, workflow
Programming Languages:
Shell
Added:
1/14/2020
Last Updated:
12/28/2020

Operations

Publications

Wahlberg E. FACEPAI: a script for fast and consistent environmental DNA processing and identification. BMC Ecology. 2019;19(1). doi:10.1186/s12898-019-0269-1. PMID:31810454. PMCID:PMC6896590.

PMID: 31810454
PMCID: PMC6896590
Funding: - The Swedish Taxonomy Initiative: dha 2014-149 4.3

Links

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