MOSGA

2.6.0 (mosga.py)

The MOSGA demonstration instance has moved from Marburg University to the University of Münster, including all uploaded user files and demonstration jobs. MOSGA has also been updated and now runs on a more robust Docker setup, which makes it easier to maintain.

	UID	Name	Files	Submission Date	Start date	End date	Mode	Status

The Modular Open-Source Genome Annotator (MOSGA) is a pipeline that easily creates draft genome annotation by a graphical user interface. It combines several specific prediction tools and generates a submission-ready annotation file.

The source code is freely available on Gitlab.com or Zenodo.com (DOI: 10.5281/zenodo.5121228). We recommend building a new docker container from the available Dockerfile in the linked Gitlab repository. MOSGA is written modular and allows easy integration of new prediction tools or even including whole third-party pipelines.

No command line

Upload a genome, choose the tools with a click and follow the job in the browser.

Submission-ready

NCBI .sqn/.tbl and ENA EMBL with Webin manifest, a submission check tells what to fix.

Modular tools

Genes, repeats, tRNAs, rRNAs, ncRNAs and telomeres, freely combined from established predictors.

Conflict resolution

Overlaps are solved by type and tool priority, removed features are listed with the reason.

Functional annotation

Product names from Swiss-Prot, eggNOG and IDTAXA, names to review are flagged.

Quality control

BUSCO, EukCC, AGAT, BlobTools and VecScreen in the same job.

Comparative genomics

ANI, gene comparison, phylogenetic trees and completeness across genomes, also of earlier jobs.

Organelle scan

Finds likely mitochondrial and plastid scaffolds and suggests to submit them as organelle sequences.

Interactive results

JBrowse 2 genome browser, summaries and all files on one results page.

One Docker image

Pinned and checksum-verified tool versions for reproducible results, self-hosted so the data stays in-house.

Convenient workflow

Uploads of several GB in resumable parts, profiles per kind of job, "Submit again", retry of failed jobs and mail notification.

Open source

MIT licensed, the code is on GitLab and Zenodo, new tools and merge requests are welcome.

For any questions or comments, please contact us: roman.martin@uni-marburg.de. We are happy to receive new suggestions or even merge requests for a pipeline extension. To provide an overview of the operation principle, we recommend reading our Gitlab wiki page.

We are providing an example data set of the draft genome annotation of Cafeteria roenbergensis BVI strain. Initially, we used an early version of MOSGA to annotate this genome (Hackl et al., 2020). Hackl, T., Martin, R., Barenhoff, K. et al. Four high-quality draft genome assemblies of the marine heterotrophic nanoflagellate Cafeteria roenbergensis. Sci Data 7, 29 (2020).

We provide two examples for the comparative genomics workflow: The Saccharomyces species phylogenetics and the Saccharomyces gene comparison. An exemplary annotation job for the organelle scanner based on the Nannochloropsis oceanica genome is here available.

Please take care about the licenses of the selected tools.

Whenever you use MOSGA please cite us:
Roman Martin , Thomas Hackl , Georges Hattab , Matthias Fischer , Dominik Heider (2020). MOSGA: Modular Open-Source Genome Annotator. Bioinformatics. 36(22-23). 5514–5515. doi: 10.1093/bioinformatics/btaa1003.

Roman Martin , Hagen Dreßler , Georges Hattab , Thomas Hackl , Matthias Fischer , Dominik Heider (2021). MOSGA 2: Comparative genomics and validation tools. Computational and Structural Biotechnology Journal. 19. 5504-5509. doi: 10.1016/j.csbj.2021.09.024.

The University of Münster hosts this MOSGA instance for demonstration purposes.
It runs on a virtualized AMD Ryzen CPU with 8 cores and 32 GB of memory.

We keep the 100 most recent job submissions online. Once this limit is exceeded, we delete the oldest job that is more than 14 days old. Incoming jobs are queued and processed as soon as possible. Jobs that occupy our hardware for more than 48 hours may be terminated. We recommend not uploading files larger than 2 GiB.

We reserve the right to analyze failed jobs in order to identify errors and to provide bug fixes and quality improvements. Even so, your results will not be shared with anyone and will be deleted regularly.

If you provide a notification email address, we may contact you if your job fails so that we can help resolve the issue.

Imprint

Universität Münster
Medizinische Fakultät (Faculty of Medicine)
Albert-Schweitzer-Campus 1, Building D3
48149 Münster, Germany
Phone: +49 251 83 52263
Fax: +49 251 83 55004
Email: dekanmed@ukmuenster.de

The Faculty of Medicine is part of the University of Münster. The University of Münster is a corporation under public law (Körperschaft des öffentlichen Rechts) and also an institution of the State of North Rhine-Westphalia. It is represented by its Rector, Prof. Dr. Susanne Menzel-Riedl.

Supervisory authority:
Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen
Völklinger Straße 49
40221 Düsseldorf, Germany

VAT ID: DE 126118759

Responsible for content pursuant to § 18 (2) MStV:
The Dean of the Faculty of Medicine
Prof. Dr. Frank Ulrich Müller
Albert-Schweitzer-Campus 1, Building D3
48149 Münster, Germany
Phone: +49 251 83 52263
Fax: +49 251 83 55004
Email: dekanmed@ukmuenster.de

Server usage