dānaSeq mag_analysis: recovery, annotation and exploration of metagenome-assembled genomes
Year: 2026
Type: preprint
Abstract: Motivation: Recovering metagenome-assembled genomes (MAGs) from an environmental co-assembly involves many tools with incompatible input formats, conflicting software dependencies, large reference databases and heterogeneous hardware requirements. Running them reproducibly on shared computing systems, and inspecting the results, is a practical obstacle for many environmental microbiology groups. Results: mag_analysis is the downstream Nextflow pipeline of the dānaSeq suite. Its inputs are an assembly FASTA and a MetaBAT2-format depth table from any assembler, optionally with sorted BAM files. It runs up to seven binners (SemiBin2, MetaBAT2, MaxBin2, LorBin, COMEBin, VAMB, TaxVAMB) and three consensus methods (DAS Tool, Binette, MAGScoT), estimates quality with CheckM2, optionally dereplicates with galah and skani, and places bins with GTDB-Tk. The assembly is annotated once with Bakta or Prokka and the annotations are mapped to bins. Optional modules cover contig taxonomy, rRNA genes, metabolism and biosynthetic gene clusters, mobile genetic elements and defence systems, eukaryotic contigs, and ECOSSDB scoring of CICES 5.2 ecosystem services and UN Sustainable Development Goals. Results are written as per-analysis tables and as a static web dashboard with eleven views. A launcher runs the pipeline from conda environments or from CPU and CUDA container images (Docker, Apptainer/Singularity), on a workstation or inside a single Slurm allocation. Finished stages are kept in the output directory, so a resubmitted job resumes where it stopped. Availability and implementation: dānaSeq is released under the MIT license at https://github.com/rec3141/danaSeq (this description corresponds to release v1.3.0, https://github.com/rec3141/danaSeq/releases/tag/v1.3.0); documentation at https://rec3141.github.io/danaSeq/.
Author: Collins, R. Eric
Institution: University of Manitoba
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7225115405