In this example tutorial, we will look at how to run BIDS App on Bacalhau. BIDS (Brain Imaging Data Structure) is an emerging standard for organizing and describing neuroimaging datasets. BIDS App is a container image capturing a neuroimaging pipeline that takes a BIDS formatted dataset as input. Each BIDS App has the same core set of command line arguments, making them easy to run and integrate into automated platforms. BIDS Apps are constructed in a way that does not depend on any software outside of the image other than the container engine.
Running imaging data structure with Bacalhau
To get started, you need to install the Bacalhau client, see more information here
For this tutorial, download file ds005.tar from this Bids dataset folder and untar it in a directory. ds005 will be our input directory in the following example.
The simplest way to upload the data to IPFS is to use a third-party service to "pin" data to the IPFS network, to ensure that the data exists and is available. To do this you need an account with a pinning service like web3.storage or Pinata or nft.storage. Once registered you can use their UI or API or SDKs to upload files.
When you pin your data, you'll get a CID which is in a format like this QmaNyzSpJCt1gMCQLd3QugihY6HzdYmA8QMEa45LDBbVPz. Copy the CID as it will be used to access your data
:::info Alternatively, you can upload your dataset to IPFS using IPFS CLI, but the recommended approach is to use a pinning service as we have mentioned above. :::
Let's look closely at the command above:
bacalhau docker run: call to bacalhau
-i ipfs://QmaNyzSpJCt1gMCQLd3QugihY6HzdYmA8QMEa45LDBbVPz:/data: mount the CID of the dataset that is uploaded to IPFS and mount it to a folder called data on the container
nipreps/mriqc:latest: the name and the tag of the docker image we are using
../data/ds005: path to input dataset
../outputs: path to the output
participant --participant_label 01 02 03: run the participant level in subjects 001 002 003
When a job is submitted, Bacalhau prints out the related job_id. We store that in an environment variable so that we can reuse it later on.
Job status: You can check the status of the job using bacalhau list.
When it says Completed, that means the job is done, and we can get the results.
Job information: You can find out more information about your job by using bacalhau describe.
Job download: You can download your job results directly by using bacalhau get. Alternatively, you can choose to create a directory to store your results. In the command below, we created a directory and downloaded our job output to be stored in that directory.
After the download has finished you should see the following contents in the results directory
To view the file, run the following command: