v.2.0.1

Job dd02ad62 - Organelle Scanner

Status
Finished
Finished at
2021/19/07 13:45
Run time
13 min

Annotation results

Your genome annotation results are ready and at least available until 2021/02/08 13:45.

Click on a button to receive the related files or view the results dynamically on the genome web browser.

SQN Submission File Genome Feature Table
View results online

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.

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.

BUSCO


Scaffold Repeats tRNA Total
Total 6966 24 6990
CP038106.1 281 0 281
CP038117.1 225 0 225
CP038128.1 288 1 289
CP038130.1 304 3 307
CP038131.1 280 0 280
CP038132.1 233 1 234
CP038133.1 310 0 310
CP038134.1 243 0 243
CP038135.1 271 0 271
CP038107.1 268 0 268
CP038108.1 270 0 270
CP038109.1 268 0 268
CP038110.1 239 1 240
CP038111.1 226 0 226
CP038112.1 236 0 236
CP038113.1 191 0 191
CP038114.1 248 0 248
CP038115.1 269 2 271
CP038116.1 222 0 222
CP038118.1 252 0 252
CP038119.1 151 1 152
CP038120.1 249 0 249
CP038121.1 189 0 189
CP038122.1 192 0 192
CP038123.1 184 0 184
CP038124.1 204 0 204
CP038125.1 177 0 177
CP038126.1 178 1 179
CP038127.1 179 0 179
CP038129.1 139 0 139
CP038137.1 0 5 5
CP038136.1 0 9 9

Taxonomy search result
Tool Hit NCBI-ID Distance
BUSCO eukaryota_odb10 2759 4
Validation File Error Summary Discrepancy Report Annotation database Snakemake configuration Snakemake log Taxonomy Search What to cite

Outputs and logs
Genome Annotation GFF Feature Table Writing Organelle Scan Mitos Plastids WindowMasker Import tRNAscan-SE 2 Import tRNAscan-SE 2 Results Barrnap Import Barrnap Results BUSCO Summary BUSCO Graph BUSCO Matches VecScreen Report VecScreen UniVec Raw Matches VecScreen UniVec Matches

What to cite
Seemann T. barrnap 0.9 : rapid ribosomal RNA prediction. https://github.com/tseemann/barrnap
Martin R, Hackl T, Hattab G, Fischer MG, Heider D. MOSGA: Modular Open-Source Genome Annotator. Bioinformatics. 2021;36(22-23):5514-5515. doi: 10.1093/bioinformatics/btaa1003
Morgulis A, Gertz EM, Schäffer AA, Agarwala R (2006). WindowMasker: window-based masker for sequenced genomes. Bioinformatics. 22(2):134‐141.
Chan, P.P., Lin, B., and Lowe, T.M (2019). tRNAscan-SE 2.0: Improved Detection and Functional Classification of Transfer RNA Genes. BioRxiv. doi: 10.1101/614032
Buels R, Yao E, Diesh CM, Hayes RD, Munoz-Torres M, Helt G, Goodstein DM, Elsik CG, Lewis SE, Stein L, Holmes IH (2016). JBrowse: a dynamic web platform for genome visualization and analysis. Genome Biol. 12;17:66. doi: 10.1186/s13059-016-0924-1
Nawrocki EP, Kolbe DL, Eddy SR. Infernal 1.0: inference of RNA alignments (2009). Bioinformatics 25(10):1335-7. Erratum in: Bioinformatics. 2009 Jul 1;25(13):1713. doi: 10.1093/bioinformatics/btp157







Upload your assembled FASTA genome file.

Priority (highest priority first)

    Functional Enrichment Analysis


    Protein-Protein Interactions Analysis


    Protein-Protein Interactions Analysis


    Choose your tools:

    Genes

    Gene
    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

    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 and Assembly Quality


    UID Name FASTA 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. 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.

    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.

    We reserve the right to analyze failed jobs to determine errors and to 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 then we could detect that could be avoided or fixed.


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