In this page, we will describe how a researcher can run Trans-Proteomics Pipeline (TPP) tutorial on BDDS Globus Galaxies. The following picture shows the various steps involved in the TPP pipeline:

  1. Create a username and password to the BDDS Globus Galaxies service running on Amazon Web Services resources here. Please use a valid email address and password to create an account.
  2. Once the user account is created, log in to the service using the username and password. 
  3. The user interface has three panels. The left hand panel is the tools panel. The tools panel has all the proteomics, NGS analysis tools that are ready to be used. The center panel is where users can view existing pipelines, build new pipelines, interactively run various analyses tools. The right hand panel is called the history panel which records all the actions users have performed and in addition can be used to access the results of the analysis.
  4. The sample datasets used in the TPP tutorial are already available in the service as a Shared Library. Click on Shared Data on the top menu panel and select Data Libraries. Select TPP Tutorial and select all the datasets. Then select "import to current history". 
  5. Once the datasets are successfully imported into the history, these datasets are available for analysis. Researcher can interactively analyze these datasets by running all the steps in the TPP tutorial individually or run the entire pipeline by selecting and executing the pre-builtTPP pipeline. In the following steps, we will show how users can import and run the existing TPP pipeline. The pipeline performs following steps: Search data with X!Tandem, Validation of Peptide-Spectrum assignments with PeptideProphet, Further peptide-level validation iProphet, Peptide Quantitation with ASAPRatio and Libra.
  6. Click on Shared Data and select "Published Workflows". Click on "TPP_workflow".
  7. This will show the TPP workflow. Click on "Import workflow" on the top right hand corner of the middle panel. Once this workflow is imported, it is now available for execution.

8. Click on the imported: TPP_workflow and select Edit. This will show the workflow that is ready to be executed. Users can select individual steps in the workflow and change any parameters as needed. As such the workflow is configured to run using the parameters specified in the original TPP workflow.

9. Click on the top right hand "gear" icon and select "Run"

10. Please make sure to select the right input datasets in Step 1, Step 2 and Step 3 of the workflow. Step 1 and 3 take the two mzML files and Step 2 takes the reference FASTA file from the tutorial. Click on Run Workflow.
11. The workflow sets up a dynamic compute cluster using Amazon EC2 resources and runs all the steps of the workflow in parallel wherever applicable. Once the workflow is run (it usually takes 5-10mins to complete), you can examine the results by clicking the little "eye" icon by the results dataset in the history panel. 

12. Users can further share the results by clicking on the gear icon on the history panel and selecting "Share or Publish History" option
13. Users can further run additional analytical tools available in the tools panel interactively or download the results for visualization