PEMA v2: addressing metabarcoding bioinformatics analysis challenges

Environmental DNA (eDNA) and metabarcoding have launched a new era in bio- eco-assessment over the last years (Ruppert et al. 2019). The simultaneous identification, at lowest taxonomic level possible, of mixture taxa from great range samples is now feasible; thus, number eDNA studies has increased radically (Deiner 2017). While experimental part can be rather challenging depending on special characteristics different studies, computational issues are considered to its major bottlenecks. Among latter, bioinformatics analysis data especially taxonomy assignment sequences fundamental challenges. Many steps required obtain taxonomically assigned matrices raw data. For most these, plethora tools available. However, each tool's execution parameters need tailored reflect experiment's idiosyncrasy; tuning proved itself (Kamenova 2020). computation capacity high-performance computing systems (HPC) frequently for such analyses. On top that, non perfect completeness correctness reference databases another important issue (Loos Based third-party tools, we developed Pipeline Metabarcoding Analysis (PEMA), HPC-centered, containerized assembly key tools. PEMA combines state-of-the art technologies algorithms with an easy get-set-use framework, allowing researchers tune thoroughly study thanks roll-back checkpoints on-demand partial pipeline features (Zafeiropoulos Once was released, there were two main pitfalls soon highlighted by users. supported 4 marker genes bounded specific databases. In this version any gene available since feature added, classifiers train user-provided database use it assignment. Fig. 1 shows related modules; all those out dashed box been release. As shown, RDPClassifier trained Midori 2 added as option, classifying not only metazoans but groups Eukaryotes case COI gene. A documentation site also PEMA.v2 containers via DockerHub SingularityHub well through Elixir Greece AAI Service. It selected LifeWatch ERIC Internal Joint Initiative ARMS will Tesseract VRE.