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LobSTR tutorial » History » Version 6

Jonathan Sheffi, 10/15/2014 03:09 PM

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h1. Running lobSTR v.3 using Arvados
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This tutorial demonstrates how to run the lobSTR pipeline using the example that Melissa Gymrek provides at her "page":http://melissagymrek.com/lobstr-code/usage.html. LobSTR is a tool for profiling Short Tandem Repeats (STRs) from high throughput sequencing data. The lobSTR publication is available here: "Gymrek M, Golan D, Rosset S, & Erlich Y. lobSTR: A short tandem repeat profiler for personal genomes. Genome Research. 2012 April 22.":http://genome.cshlp.org/content/early/2012/04/19/gr.135780.111.abstract This tutorial introduces the following Arvados features:
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* How to run lobSTR v.3 using Arvados
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* How to access your pipeline results.
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* How to browse and select input your data for lobSTR and submit re-run the pipeline.
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# Start at the "Curoverse":https://curoverse.com/ website and click Log In at the top. We currently support all Google / Google Apps accounts for authentication. By simply choosing a Google-based account, your account will be automatically created and redirect to the "Arvados Workbench":https://workbench.qr1hi.arvadosapi.com/.
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# In the *Active pipelines* panel, click on the *Run a pipeline...* button. Doing so opens a dialog box titled *Choose a pipeline to run*.
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# Select *lobstr v.3* and click the *Next: choose inputs* button. Doing so loads a new page to supply the inputs for the pipeline.
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# The default inputs from Melissa's git repository are already pre-loaded. Click on the *Run* button. The page updates to show you that the pipeline has been submitted to run on the Arvados cluster.
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# After the pipeline starts running, you can track its progress by watching log messages from jobs.  This page refreshes automatically.  You will see a complete label under the job the column when the pipeline completes successfully. The current run time of the job in CPU and clock hours is also displayed. You can view individual job details by clicking on the job name.
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# Once the job is finished, the output can be viewed to the right of the run time.
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# Click on the download button to the right of the file to download your results, or the magnifying glass to quickly view your results.
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h2. Uploading data and using it on Arvados
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Full documentation can be found "here":http://doc.arvados.org/user/tutorials/tutorial-keep.html
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# Install the "Arvados Python SDK":http://doc.arvados.org/sdk/python/sdk-python.html on the system from which you will upload the data (such as your workstation, or a server containing data from your sequencer). Doing so will install the Arvados file upload tool, arv-put. 
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# Navigate back to your Workbench dashboard and create a new project by clicking on the Projects dropdown menu and clicking Home. 
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# Click on [+ Add a subproject]. Feel free to edit the Project name or description by clicking the pencil to the right of the text.
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# To add data, return back to your shell and use the command arv-put as well as the name of your file and the tag --project-uuid qr1hi-xxxxx-yyyyyyyyyyyyyyy. The qr1hi tag can be found in the url of your new project.
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# The output value xxxxxxxxxxxxxxxxxxxx+yyyy is the Arvados collection locator that uniquely describes this file.
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# Once that is uploaded, navigate back to the dashboard and click on *Run a pipeline...* and choose lobstr v.3.
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# You can change the input by clicking on [Choose] next to the *Input fastq collection ID*.
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# Click on the Dropdown menu and click on your created project and choose your desired input collection. Click OK and Run to run lobSTR v.3 on your data!