BIDS-Apps/ndmg

Name: ndmg

Owner: BIDS Apps

Description: BIDS app for NeuroData's MRI to Graphs pipeline

Created: 2016-08-02 15:18:55.0

Updated: 2018-01-30 21:50:31.0

Pushed: 2018-01-30 21:54:39.0

Homepage: http://m2g.io

Size: 56

Language: TeX

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README

ndmg

NeuroData?s MR Graphs package, ndmg (pronounced ?nutmeg?), is the successor of the MRCAP, MIGRAINE, and m2g pipelines. ndmg combines dMRI and sMRI data from a single subject to estimate a high-level connectome reliably and scalably.

Documentation

Please read the official ndmg docs.

Error Reporting

Experiencing problems? Please open an issue and explain what's happening so we can help.

Acknowledgement

When using this pipeline, please acknowledge us with the citations in the attached bibtex file.

Instructions

The bids/ndmg Docker container enables users to run end-to-end connectome estimation on structural MRI right from container launch. The pipeline requires that data be organized in accordance with the BIDS spec. If the data you wish to process is available on S3 you simply need to provide your s3 credentials at build time and the pipeline will auto-retrieve your data for processing.

To get your container ready to run just follow these steps:

(A) I do not wish to use S3:

• In your terminal, type:

  cker pull bids/ndmg
  

(B) I wish to use S3:

• Add your secret key/access id to a file called credentials.csv in this directory on your local machine. A dummy file has been provided to make the format we expect clear. (This is how AWS provides credentials)
• In your terminal, navigate to this directory and type:

  cker build -t <yourhandle>/ndmg .
  

Now we're ready to launch our instances and process some data!

Like a normal docker container, you can startup your container with a single line. Let's assume I am running this and I wish to use S3, so my container is called gkiar/ndmg. If you don't want to use S3, you can replace gkiar with bids and ignore the S3 related flags for the rest of the tutorial.

I can start my container with:

cker run -ti bids/ndmg
e: ndmg_bids [-h]
             [--participant_label PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]]
             [--bucket BUCKET] [--remote_path REMOTE_PATH]
             bids_dir output_dir {participant}
_bids: error: too few arguments

We should've noticed that I got an error back suggesting that I didn't properly provide information to our container. Let's try again, with the help flag:

cker run -ti bids/ndmg:v4 -h

e: ndmg_bids [-h]
             [--participant_label PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]]
             [--bucket BUCKET] [--remote_path REMOTE_PATH]
             bids_dir output_dir {participant}

 is an end-to-end connectome estimation pipeline from sMRI and DTI images

tional arguments:
ds_dir              The directory with the input dataset formatted
                    according to the BIDS standard.
tput_dir            The directory where the output files should be stored.
                    If you are running group level analysis this folder
                    should be prepopulated with the results of the
                    participant level analysis.
articipant}         Level of the analysis that will be performed. Multiple
                    participant level analyses can be run independently
                    (in parallel) using the same output_dir.

onal arguments:
, --help            show this help message and exit
participant_label PARTICIPANT_LABEL [PARTICIPANT_LABEL ...]
                    The label(s) of the participant(s) that should be
                    analyzed. The label corresponds to
                    sub-<participant_label> from the BIDS spec (so it does
                    not include "sub-"). If this parameter is not provided
                    all subjects should be analyzed. Multiple participants
                    can be specified with a space separated list.
bucket BUCKET       The name of an S3 bucket which holds BIDS organized
                    data. You must have built your bucket with credentials
                    to the S3 bucket you wish to access.
remote_path REMOTE_PATH
                    The path to the data on your S3 bucket. The data will
                    be downloaded to the provided bids_dir on your
                    machine.

Cool! That taught us some stuff. So now for the last unintuitive piece of instruction and then just echoing back commands I'm sure you could've figured out from here: in order to share data between our container and the rest of our machine, we need to mount a volume. Docker does this with the -v flag. Docker expects its input formatted as: -v path/to/local/data:/path/in/container. We'll do this when we launch our container, as well as give it a helpful name so we can locate it later on. Finally:

er run -ti --name ndmg_test --rm -v ./data:${HOME}/data bids/ndmg ${HOME}/data/ ${HOME}/data/outputs participant --participant_label 01 -b mybucket -r path/on/bucket/