Your genome annotation results are ready and at least available until 2021/19/01 11:27.
Click on a button to receive the related files or view the results dynamically on the genome web browser.
SQN Submission File Genome Feature TablePlease cite always:
Roman Martin, Thomas Hackl, Georges Hattab, Matthias G Fischer, Dominik Heider (2020). MOSGA: Modular Open-Source Genome Annotator. Bioinformatics. doi: 10.1093/bioinformatics/btaa1003.
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.
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.
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).
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. doi: 10.1093/bioinformatics/btaa1003.
This MOSGA instance is hosted by the Philipps University of Marburg for demonstration purposes.
It runs on an AMD Zen processor with 16 threads and 32 GB of memory.
Processed jobs that are older than 14 days will be deleted automatically.
Incoming jobs are queued and processed as soon as possible. Jobs that stress our hardware longer than 48 hours could be terminated.
Uploading jobs could be aborted depending on your bandwidth and the upload duration. Therefore we recommend not to upload files that are larger than 200 MiB.