Welcome

Hey there!
This is the PEMA main site for how to use and further metabarcoding tips and hints!
This documentation is about the current, Nextflow-based PEMA. For PEMA v2.x (BigDataScript, run from a Docker or Singularity image), see the previous version of this documentation.

PEMA is a pipeline for environmental DNA metabarcoding analysis of the 16S/18S rRNA, 12S rRNA, ITS and COI marker genes. It takes paired-end Illumina reads and returns an ASV or OTU table with the taxonomy of each ASV/OTU and its abundance in each sample.

PEMA is now written in Nextflow. Every step runs in its own container, so all you need is Nextflow and a container engine (Docker, Podman, Singularity or Apptainer); the containers are downloaded automatically. The same command runs PEMA on a laptop, a server or an HPC cluster, and an interrupted or changed run can be resumed from where it stopped.

Here is what PEMA does:

Step	Tool
Primer removal (ITS only)	cutadapt
Quality control and merging of the read pairs	fastp
Dereplication	VSEARCH
ASV inference, or OTU clustering with chimera removal	Swarm or DADA2, or VSEARCH
Taxonomy assignment	crest4 or RDPClassifier, with built-in, PEMA-trained or your own databases
Mapping to NCBI Taxonomy (optional)	NCBI Datasets

To start, see Get PEMA and Basics for running PEMA.

Here is the PEMA GitHub repository if you want to have a look on the source code and why not, to contribute to!

For any running issues you may have, or for any further features you would like to see included on PEMA, you can reach us through the PEMA Gitter community, by opening an issue, or at pema@hcmr.gr .

Thanks for your interest on PEMA! Keep metabarcoding!

The PEMA team

To cite PEMA:
Zafeiropoulos H, Viet HQ, Vasileiadou K, Potirakis A, Arvanitidis C, Topalis P, Pavloudi C, Pafilis E. PEMA: a flexible Pipeline for Environmental DNA Metabarcoding Analysis of the 16S/18S ribosomal RNA, ITS, and COI marker genes. GigaScience. 2020 Mar;9(3):giaa022.