Personal tools

Examples

Essentially mGene.web can be used in three different ways: 1) If you simply want it as a black-box tool to get your sequence annotated, you should use the monolithic tools mGeneTrain, mGenePredict and mGeneEval. 2) If you would like to get a little more involved, perhaps inspect intermediate results, like transcription start site predictions and so on, you should use the pre-defined workflows. 3) You might not even be interested in the complete gene finding process, but only in a subtask, then you should have a look at the individual mGene.web Modules. With those you can also build your own workflows. These options are explained in more detail along the lines of a few examples.

Load the Supplied Example Data

  1. go to http://galaxy.fml.mpg.de
  2. in the toolbar at the left, open "mGene.web"
  3. klick on "Examples and Instructions" => the organism "C. elegans" is already pre-selected
  4. press "execute" to load the example data => three new objects will appear in the object list on the right
    • Information about the datasets
    • Genome Annotation in GFF3 format
    • Genome Sequence in FASTA format

mGeneTrain: Train the Gene Finder

  1. from "mGene.web" in the toolbar, select "mGeneTrain"
  2. in the input box (beige, labeled "mGeneTrain") select the FASTA file and the GFF3 annotation from the C. elegans example
  3. press "execute"
  4. be patient -- training a full gene finder is a very complex computation and will take a few hours

mGenePredict: Find Genes in Other Genomic DNA

  1. use "Upload file" in the toolbar to upload a FASTA file
  2. activate "mGene.web"->"mGenePredict" from the toolbar
  3. select your FASTA data file and your previously trained mGene predictor and "execute"

Libraries

Via the galaxy-framework we offer pretrained signal, content and gene-structure classifiers for an increasing number of organisms. To obtain such a classifier please follow the following simple steps.

  1. click on Libraries on the top panel of your galaxy environment => a list of all available libraries is shown
  2. click on one of the libraries from the list => a list of datasets and classifiers opens
  3. select a data set of your choice and click on go to import it

Please note that all the classifiers provide additional information once you have uploaded them, e.g.:

`Trained "don" classifier`

  • based on 3381 labeled examples (272 positive, 3109 negative)
  • using 5-fold cross-validation for model-selection from 1 models (inner cv loop)
  • using 5-fold cross-validation for obtaining unbiased predictions (outer cv loop)

`Performance`

  • Average area under ROC curve on test splits: 0.995
  • Average area under PRC curve on test splits: 0.940

Using pre-defined Workflows

We provide a number of predefined workflows that combine different parts of our system to complete certain tasks. The workflows are described in detail here.

Note: To import one of these workflows you have to login to the galaxy system

To run a pre-defined workflow do the folliwing steps:

  1. click on User on the top panel of your galaxy environment
  2. if you are already registered, log in, if not, register
  3. use one of the links provided here to import one of the workflows
  4. in the list Workflows shared with you by others you should now find the imported workflow
  5. click on the respective workflow
  6. chose the required input data files (if there is nothing to chose from you first need to upload the data, see above)
  7. click on Run workflow at the bottom of the page
  8. go back to Analyze Data at the top panel of your galaxy environment
  9. you should now be able to observe the progress of the called modules.

Changing pre-defined Workflows

  1. click on the Workflow button in the top panel of the galaxy system
  2. click on the arrow on the right hand side of your imported workflow and select clone
  3. click on the arrow of your cloned workflow and select edit
  4. now the workflow editor opens and you can inspect and modify the workflow
  5. you might also want to have a look at the individual mGene.web Modules (left panel). they can be added to the workflow by clicking on them.
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