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MetaWorks is a flexible multi-marker metabarcode pipeline for processing paired-end Illumina reads from raw fastq.gz files to taxonomic assignments.

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MetaWorks: A Multi-Marker Metabarcode Pipeline

DOI

MetaWorks generates exact sequence variants and/or operational taxonomic units and taxonomically assigns them. Supports a number of popular metabarcoding markers: COI, rbcL, ITS, SSU rRNA, and 12S SSU mtDNA. See the MetaWorks website for quickstart guides, additional pipeline details, FAQs, and a step-by-step tutorial that includes installation.

Installation

MetaWorks runs at the command-line on linux x86-64 in a conda environment (provided).

Instructions for installing conda (if not already installed).

Instructions for installing ORFfinder if pseudogene-filtering will be run (optional).

Instructions for installing MetaWorks and activating the MetaWorks conda environment.

Instructions on where to find custom-trained classifiers that can be used with MetaWorks.

Documentation

A quickstart guide to various workflows.

A detailed explanation of MetaWorks workflows.

A tutorial provides step-by-step instructions on how to prepare your environment and get started quickly using the provided test data.

NEW We added answers to some frequently asked questions (FAQs) about MetaWorks and data analysis to the MetaWorks website.

How to cite

If you use this dataflow or any of the provided scripts, please cite the MetaWorks paper:
Porter, T. M., & Hajibabaei, M. (2022). MetaWorks: A flexible, scalable bioinformatic pipeline for high-throughput multi-marker biodiversity assessments. PLOS ONE, 17(9), e0274260. doi: 10.1371/journal.pone.0274260

You can also site this repository: Teresita M. Porter. (2020, June 25). MetaWorks: A Multi-Marker Metabarcode Pipeline (Version v1.10.0). Zenodo. http://doi.org/10.5281/zenodo.4741407

If you use this dataflow for making COI taxonomic assignments, please cite the COI classifier publication:
Porter, T. M., & Hajibabaei, M. (2018). Automated high throughput animal CO1 metabarcode classification. Scientific Reports, 8, 4226.

If you use the pseudogene filtering methods, please cite the pseudogene publication: Porter, T.M., & Hajibabaei, M. (2021). Profile hidden Markov model sequence analysis can help remove putative pseudogenes from DNA barcoding and metabarcoding datasets. BMC Bioinformatics, 22: 256.

If you use the RDP classifier, please cite the publication:
Wang, Q., Garrity, G. M., Tiedje, J. M., & Cole, J. R. (2007). Naive Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy. Applied and Environmental Microbiology, 73(16), 5261–5267. doi:10.1128/AEM.00062-07

Last updated: September 30, 2022

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MetaWorks is a flexible multi-marker metabarcode pipeline for processing paired-end Illumina reads from raw fastq.gz files to taxonomic assignments.

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