Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research
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PEMA is a HPC-centered, containerized assembly of key metabarcoding analysis tools. It supports the downstream analysis of four marker genes (16S/18S rRNA, ITS and COI) but also, by allowing the user to train the classifiers with custom reference databases, it can be used for further marker genes. By combining state-of-the art technologies and algorithms with an easy to get-set-use framework, PEMA allows researchers to tune thoroughly each study thanks to roll-back checkpoints and on-demand partial pipeline execution features.
This is an input parameter file used for running PEMA on COI marker gene data in the ARMS Internal Joint Initiative workflow. It is a tsv file that can be uploaded in order to specify which sequence (which column gene_18S, gene_COI, gene_ITS) is chosen. It is a well-defined template and the user is required to modify certain fields only.
This service aims at running various statistical analyses in RvLab on the produced data produced in this workflow. It represents the Step 10 of the ARMS Workflow within the Internal Joint Initiative.
Background Monitoring hard-bottom marine biodiversity can be challenging as it often involves non-standardised sampling methods that limit scalability and inter-comparison across different monitoring approaches. Therefore, it is essential to implement standardised techniques when assessing the status of and changes in marine communities, in order to give the correct information to support management policy and decisions, and to ensure the most appropriate level of protection for the biodiversity in each ecosystem. Biomonitoring methods need to comply with a number of criteria including the implementation of broadly accepted standards and protocols and the collection of FAIR data (Findable, Accessible, Interoperable, and Reusable). Introduction Artificial substrates represent a promising tool for monitoring community assemblages of hard-bottom habitats with a standardised methodology. The European ARMS project is a long-term observatory network in which about 20 institutions distributed across 14 European countries, including Greenland and Antarctica, collaborate. The network consists of Autonomous Reef Monitoring Structures (ARMS) which are deployed in the proximity of marine stations and Long-term Ecological Research sites. ARMS units are passive monitoring systems made of stacked settlement plates that are placed on the sea floor. The three-dimensional structure of the settlement units mimics the complexity of marine substrates and attracts sessile and motile benthic organisms. After a certain period of time these structures are brought up, and visual, photographic, and genetic (DNA metabarcoding) assessments are made of the lifeforms that have colonised them. These data are used to systematically assess the status of, and changes in, the hard-bottom communities of near-coast ecosystems. Aims ARMS data are quality controlled and open access, and they are permanently stored (Marine Data Archive) along with their metadata (IMIS, catalogue of VLIZ) ensuring data fairness. Data from ARMS observatories provide a promising early-warning system for marine biological invasions by: i) identifying newly arrived Non-Indigenous Species (NIS) at each ARMS site; ii) tracking the migration of already known NIS in European continental waters; iii) monitoring the composition of hard-bottom communities over longer periods; and iv) identifying the Essential Biodiversity Variables (EBVs) for hard-bottom fauna, including NIS. The ARMS validation case was conceived to achieve these objectives: a data-analysis workflow was developed to process raw genetic data from ARMS; end-users can select ARMS samples from the ever-growing number available in collection; and raw DNA sequences are analysed using a bioinformatic pipeline (P.E.M.A.) embedded in the workflow for taxonomic identification. In the data-analysis workflow, the correct identification of taxa in each specific location is made with reference to WoRMS and WRiMS, webservices that are used to check respectively the identity of the organisms and whether they are introduced.