accession 4.7.1

Tool to submit genomics pipeline outputs to the ENCODE Portal

accession is a Python module and command line tool for submitting genomics pipeline analysis output files and metadata to the ENCODE Portal.

Installation

Note: installation requires Python >= 3.6

$ pip install accession

Next, provide your API keys from the ENCODE portal:

$ export DCC_API_KEY=XXXXXXXX
$ export DCC_SECRET_KEY=yyyyyyyyyyy

It is highly recommended to set the DCC_LAB and DCC_AWARD environment variables for ease of use. These correspond to the lab and award identifiers given by the ENCODE portal, e.g. /labs/foo/ and U00HG123456, respectively.

$ export DCC_LAB=XXXXXXXX
$ export DCC_AWARD=yyyyyyyyyyy

If you are accessioning workflows produced using the Caper local backend, then installation is complete. However, if using WDL metadata from pipeline runs on Google Cloud, you will also need to authenticate with Google Cloud. Run the following two commands and follow the prompts:

$ gcloud auth login --no-launch-browser
$ gcloud auth application-default login --no-launch-browser

If you would like to be able to pass Caper workflow IDs or labels you will need to configure access to the Caper server. If you are invoking accession from a machine where you already have a Caper set up, and you have the Caper configuration file available at ~/.caper/default.conf, then there is no extra setup required. If the Caper server is on another machine, you will need so configure HTTP access to it by setting the hostname and port values in the Caper conf file.

(Optional) Finally, to enable using Cloud Tasks to upload files from Google Cloud Storage to AWS S3, set the following two environment variables. If one or more of them is not set, then files will be uploaded using the same machine that the accessioning code is run from. For more information on how to set up Cloud Tasks and the upload service, see the docs for the gcs-s3-transfer-service

$ export ACCESSION_CLOUD_TASKS_QUEUE_NAME=my-queue
$ export ACCESSION_CLOUD_TASKS_QUEUE_REGION=us-west1

To accession workflows produced on AWS backend you will need to set up AWS credentials. The easiest way to do this is to install the AWS CLI and run aws configure

Usage

$ accession -m metadata.json \
            -p mirna \
            -s dev

Please see the docs for greater detail on these input parameters.

Deploying on Google Cloud

First authenticate with Google Cloud via gcloud auth login if needed. Then install the API client with pip install google-api-python-client, it is recommended to do this inside of a venv. Finally, create the firewall rule and deploy the instance by running python deploy.py –project $PROJECT. This will also install the accession package. Finally, SSH onto the new instance and run gcloud auth login to authenticate on the instance.

For Caper integration, once the instance is up, SSH onto it and create the Caper conf file at ~/.caper/default.conf, use the private IP of the Caper VM instance as the hostname and use 8000 for the port. For the connection to work the Caper VM will need to have the tag caper-server. Also note that the deployment assumes the Cromwell server port is set to 8000.

AWS Notes

To enable S3 to S3 copy from the pipeline buckets to the ENCODE buckets, ensure that the pipeline bucket policy grants read access to the ENCODE account. Here is an example policy:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "DelegateS3AccessGet",
            "Effect": "Allow",
            "Principal": {
                "AWS": [
                    "arn:aws:iam::618537831167:root",
                    "arn:aws:iam::159877419961:root"
                ]
            },
            "Action": "s3:GetObject",
            "Resource": "arn:aws:s3:::PIPELINE-BUCKET/*"
        },
        {
            "Sid": "DelegateS3AccessList",
            "Effect": "Allow",
            "Principal": {
                "AWS": [
                    "arn:aws:iam::618537831167:root",
                    "arn:aws:iam::159877419961:root"
                ]
            },
            "Action": "s3:ListBucket",
            "Resource": "arn:aws:s3:::PIPELINE-BUCKET"
        }
    ]
}

Project Information

accession is released under the MIT license, documentation lives in readthedocs, code is hosted on github and the releases on PyPI.