This walkthrough provides a simple example of how to set-up and run the HMP Unified Metabolic Analysis Network (HUMAnN) Pipeline using the web-browser accessible CloVR dashboard. The HUMAnN Pipeline is used to efficiently and accurately determine the presence/absence and abundance of microbial pathways in a community from metagenomic data. For this walkthrough, we shall utilize genes from the Anterior Nares body site (sample SRS019215). This walkthrough also demonstrates how to run the pipeline using the cloud for computational support. The HUMAnN SOP provides a detailed description of this pipeline.
Note: This pipeline is not yet available on the lastest CloVR release (clovr-1.0-RC5, Nov. 2012). For now, you can access this pipeline by requesting an account at www.diagcomputing.org. After you login, select “Start CloVR” from the “My Account” drop-down. This will launch a new CloVR VM. Continue with the walkthrough from the Add input datasets to the pipeline step.
Getting started with CloVR
Installing and setting up CloVR is a one-time process. If you have done this before, you may skip to the next step – Setting up input dataset.
CloVR is run using a local desktop client. Visit the Getting started with CloVR page to download and install the client. Once the CloVR virtual machine is set up and launched, you should see a screen similar to Figure 1.
Figure 1. CloVR desktop client
Start the CloVR web interface
First check the CloVR desktop window for the IP address of your virtual machine (VM). Then enter this IP address in a web browser as shown in Figure 2.
Figure 2. Accessing the CloVR web interface
Add cloud credentials to the pipeline
If you do not need additional computational support, you may skip to the next step – Setting up input dataset.
For additional computational support, visit the Adding Credentials page for steps on how to add DIAG credentials. DIAG is an academic cloud which is free for researchers. Alternatively, you could run the pipeline on Amazon EC2 or using other cloud computing providers. Once the your DIAG credentials are setup, you should see it listed within the credentials tab as shown in Figure 3.
Setting up input dataset
Prepare input datasets
This pipeline requires an input file in FASTA format. Move the input file into the user_data folder located within the clovr-standard-* image directory. This will enable us to easily access the data through the CloVR dashboard.
Before starting a pipeline, you must add your datasets to the CloVR VM as “Tags”. To add tags, click “Add” on the web interface.
Then click on “Select file from image”, which will open a sub-window where you can select a FASTA file for upload into the VM. Alternatively, you can use “Browse” in the “Upload File” window to find and select files from anywhere on your local computer.
Select “Nucleotide FASTA” from the “File Type” drop-down menu and name your dataset, e.g. as “input_reads”. Add an optional description of your dataset. Click “Tag” to upload the data to CloVR. A “Completed Successfully” window should appear to indicate that your datasets was added to the CloVR VM and the new dataset should be listed under “Data Sets” on the web interface.
Figure 6. Setting up input dataset
The tagged datasets will appear as a “Tag” on the CloVR web interface. Multiple files will listed under the same “Tag” name.
Figure 7. Tagged Datasets
Pipeline setup and execution
To initialize a new pipeline run, click on the “Other Protocols” drop-down as shown in the figure below. Then select “clovr_humann”.
This will open the pipeline configuration window. For the input datasets select the tag corresponding to the input file.
Select “local” or “DIAG” credentials from the “Account” drop-down menu.Provide a name to recognize your pipeline in the web interface home page as “Pipeline Description”, e.g. “SRS019215_test″.
Check your input by clicking “validate”. If the validation is successful, start the pipeline by clicking “submit”.
After a successful pipeline submission, the web interface will change to the “Home” page where the new pipeline will be listed as “Status: running.”
Monitoring the pipeline
Your pipeline should now appear in the Pipelines window in the CloVR dashboard along with its status. Occasionally, the pipeline may idle for a minute or two before running. You can click on the pipeline to get a description, input parameters, and hyperlinks to more advanced workflow interfaces like Ergatis. Clicking on the [Pipeline #] headers in the “Pipeline Information” window will open the Ergatis “Workflow creation and monitoring interface” in a separate browser window, which provides useful information for troubleshooting of failed pipeline runs.
Accessing the outputs
Once the pipeline completes, the results can be downloaded from this CloVR dashboard by clicking on the Outputs tab (Figure 10). All results files are created as compressed archives (.tar.gz), which can be extracted using the Finder in Mac OS X, the Tar utility in Unix or programs such as WinZipor WinRAR, in Windows.
See the HUMAnN SOP for a full description of the output files produced.