v.2.1.5

Job 9c2cb5d3 - Saccharomyces species

Finished in
1 h 44 min

Comparative Genomics results

Your prediction results are ready and at least available until 2021/13/07 11:22.

Click on a button to receive the related results.

Please cite always:

  • Roman Martin, Thomas Hackl, Georges Hattab, Matthias G 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 G 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.

Do you have some questions, issues or just would like to give us feedback? Please don't hesitate to write us or feel free to open a new issue on Gitlab.

Upload your assembled FASTA eukaryotic genome file.

Priority (highest priority first)

    CpG island detection


    CpG island detection


    Splicing site detection


    Functional Enrichment Analysis


    Protein-Protein Interactions Analysis


    Protein-Protein Interactions Analysis



    Choose your tools:

    Genes

    Gene
    Protein-coding genes

    Prediction of gene locations and splice sites.

    Mode of work

    Evidence-based or ab initio prediction.

    Functional Annotation

    Functional gene prediction.

    Repeats

    Repeats

    Detection of repeating sequences.

    tRNAs

    tRNA

    Prediction of tRNA sequences.

    rRNAs

    rRNA

    Search for rRNA sequence matches.

    Assembly Validation

    Genome Completeness

    Validate genome completeness.

    Quality-Control

    Contamination detection.


    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.

    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 orcid, Thomas Hackl orcid, Georges Hattab orcid, Matthias Fischer orcid, Dominik Heider orcid (2020). MOSGA: Modular Open-Source Genome Annotator. Bioinformatics. 36(22-23). 5514–5515. doi: 10.1093/bioinformatics/btaa1003.

    Roman Martin orcid, Hagen Dreßler orcid, Georges Hattab orcid, Thomas Hackl orcid, Matthias Fischer orcid, Dominik Heider orcid (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 Philipps University of Marburg hosts this MOSGA instance for demonstration purposes. It runs on an AMD Zen processor with 16 threads and 32 GB of memory.

    We preserve the last 100 job submissions online until that limit exceeds. After that, we delete the oldest submission job that is at least more aged than 14 days. Incoming jobs are queued and processed as soon as possible. Computation tasks that stress our hardware longer than 48 hours could be terminated. We recommend not to upload files that are larger than 2 GiB.

    We reserve the right to analyze failed jobs to determine errors and provide bug fixes and quality improvements. Your results will still not be shared and regularly delete.

    If you provide a notification email address, we may contact you if your job failed to avoid or fix the issue.


    Server usage