ARMS-MBON 18S rRNA and COI gene metabarcoding: scanning for non-indigenous species v1
Authors: Daraghmeh Nauras 
Published: October 2024

This workflow details how COI and 18S rRNA gene raw amplicon sequencing data from the European ARMS programme (ARMS-MBON) can be processed bioinformatically to generate read count and taxonomy tables of molecular operational taxonomic units (mOTUs) for the identification of (marine) non-indigenuous species (NIS). However, the end products may also be used for any other diversity analyses that suit the user. The pipeline may also be adjusted to work with amplicon sequence variants (ASVs) instead of mOTU by omitting and ajdusting certain steps. The data used here comprise all publicly available COI and 18S sequencing data from ARMS-MBON as of February 2024. Processes described in this pipeline were executed on Unix and Windows OS. Certain steps (especially software installations etc.) may differ when run on different operating systems. Some computationally intensive steps were run on a high-performance computing cluster. This is noted in the respective section of this workflow. Note that in this workflow, separate directories were created for each marker gene. Make sure that the input files required (i.e., the files produced in the correspoding preceding step) are in the respective directory. References to all data, software, packages and databases used in this workflow (please cite any of the tools used in your analysis): ARMS-MBON (Obst et al., 2020) R v4.1.0 and v4.3.1 (R Core Team, 2021, 2023) (v4.3.1 was used for dada2 processing and COI numt-removal) RStudio 2022.07.1 (RStudio Team, 2022) cutadapt v4.5 (Martin, 2011) Git v2.37.3 (Chacon & Straub, 2014) Python v3.11.4 (Van Rossum & Drake, 2009) MACSE v2.05 (Ranwez et al., 2018) swarm v3.0.0 (Mahé et al., 2015) NCBI BLAST (Johnson et al., 2008) BLAST+ release 2.11.0 (Camacho et al., 2009) BOLD (Ratnasingham & Hebert, 2007) BOLDigger-commandline v2.2.1 (Buchner & Leese, 2020) SeqKit v2.5.1 (Shen et al., 2016) MIDORI2 (Leray et al., 2022) MIDORI2 webserver (Leray et al., 2018) GenBank release 257 (Benson et al., 2012) RDP classifier (Wang et al., 2007) Silva taxonomic training data formatted for DADA2 (Callahan, 2018) (Silva v132; Quast et al., 2013) SILVA v128 and v132 dada2 formatted 18s 'train sets' (Morien & Parfrey, 2018) (Silva v128 and v132; Quast et al., 2013)Protist Ribosomal Reference database (PR2) v5.0.0 (Guillou et al., 2013)World Register of Marine Species (WoRMS) (Ahyong et al., 2023) World Register of Introduced Marine Species (WRiMS) (Rius et al., 2023) Microsoft Excel 2016 (Microsoft Corporation, 2016) R packages: argparse v2.2.2 (Davis, 2023) dada2 v1.28.0 (Callahan et al., 2016) ShortRead v1.58.0 (Morgan et al., 2009) Biostrings v2.68.1 (Pagés et al., 2020) ggplot2 v3.4.2 and v3.4.3 (Wickham, 2016) (v3.4.3 was used in the dada2 workflow to plot read quality profiles) ensembleTax v1.2.2 (Catlett et al., 2023) tidyr v1.3.0 (Wickham et al., 2023) dplyr v1.0.9 and v1.1.3 (Wickham et al., 2022, 2023) (v1.1.3 was used during COI numt-removal) stringr v1.5.0 (Wickham, 2022) devtools v2.4.3 (Wickham et al., 2021) hiReadsProcessor v1.29.1 and v1.36.0 (Malani, 2021) (v1.36.0 was used during COI numt-removal) seqinr v4.2.30 (Charif & Lobry, 2007) remotes v2.4.2 (Csárdi et al., 2021) LULU v0.1.0 (Frøslev et al., 2017) readxl v1.4.0 (Wickham & Bryan, 2022) phyloseq v1.36.0 (McMurdie & Holmes, 2013) vegan v2.6.2 (Oksanen et al., 2023) ggpubr v0.4.0 (Kassambara, 2020) data.table v1.14.2 (Dowle & Srinivasan, 2021) xlsx v0.6.5 (Dragulescu & Arendt, 2020) plyr v1.8.7 (Wickham, 2011) geosphere v1.5.18 (Hijmans 2022) Bibliography: Ahyong, S., Boyko, C. 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