Version: v.1.1.4

Upload your assembled FASTA genome file.

Priority (highest priority first)

    Choose your prediction tools

    Genes

    Gene prediction tool

    Prediction of gene locations and splicing sites.

    Mode of work

    Evidence-based or ab initio prediction

    Functional prediction

    Functional gene prediction by comparison of protein databases.

    Repeats

    Detection of repeating sequences.

    tRNAs

    Prediction of tRNA sequences.

    rRNAs

    Search for rRNA sequence matches.


    No entries

    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 wiki page option Gitlab.

    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).

    A preprint version of the MOSGA publication is already online at Arxiv.org.
    Please take care about the licenses of the selected tools.

    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.