AWS HealthOmics Tools

Tools for working with the Amazon Omics Service.

Using the Omics Transfer Manager

Installation

Installation Amazon Omics Tools is available through pypi. To install, type:

pip install amazon-omics-tools

Basic Usage

The TransferManager class makes it easy to download files for an Omics reference or read set. By default the files are saved to the current directory, or you can specify a custom location with the directory parameter.

import boto3
from omics.common.omics_file_types import ReadSetFileName, ReferenceFileName, ReadSetFileType
from omics.transfer.manager import TransferManager
from omics.transfer.config import TransferConfig

REFERENCE_STORE_ID = "<my-reference-store-id>"
SEQUENCE_STORE_ID = "<my-sequence-store-id>"

client = boto3.client("omics")
manager = TransferManager(client)

# Download all files for a reference.
manager.download_reference(REFERENCE_STORE_ID, "<my-reference-id>")

# Download all files for a read set to a custom directory.
manager.download_read_set(SEQUENCE_STORE_ID, "<my-read-set-id>", "my-sequence-data")

Download specific files

Specific files can be downloaded via the download_reference_file and download_read_set_file methods. The client_fileobj parameter can be either the name of a local file to create for storing the data, or a TextIO or BinaryIO object that supports write methods.

# Download a specific reference file.
manager.download_reference_file(
    REFERENCE_STORE_ID,
    "<my-reference-id>",
    ReferenceFileName.INDEX
)

# Download a specific read set file with a custom filename.
manager.download_read_set_file(
    SEQUENCE_STORE_ID,
    "<my-read-set-id>",
    ReadSetFileName.INDEX,
    "my-sequence-data/read-set-index"
)

Upload specific files

Specific files can be uploaded via the upload_read_set method. The fileobjs parameter can be either the name of a local file, or a TextIO or BinaryIO object that supports read methods. For paired end reads, you can define fileobjs as a list of files.

# Upload a specific read set file.
read_set_id = manager.upload_read_set(
    "my-sequence-data/read-set-file.bam",
    SEQUENCE_STORE_ID,
    "BAM",
    "name",
    "subject-id",
    "sample-id",
    "<my-reference-arn>",
)

# Upload paired end read set files.
read_set_id = manager.upload_read_set(
    ["my-sequence-data/read-set-file_1.fastq.gz", "my-sequence-data/read-set-file_2.fastq.gz"],
    SEQUENCE_STORE_ID,
    "FASTQ",
    "name",
    "subject-id",
    "sample-id",
    "<my-reference-arn>",
)

Subscribe to events

Transfer events: on_queued, on_progress, and on_done can be observed by defining a subclass of OmicsTransferSubscriber and passing in an object which can receive events.

class ProgressReporter(OmicsTransferSubscriber):
    def on_queued(self, **kwargs):
        future: OmicsTransferFuture = kwargs["future"]
        print(f"Download queued: {future.meta.call_args.fileobj}")

    def on_done(self, **kwargs):
        print("Download complete")

manager.download_read_set(SEQUENCE_STORE_ID, "<my-read-set-id>", subscribers=[ProgressReporter()])

Threads

Transfer operations use threads to implement concurrency. Thread use can be disabled by setting the use_threads attribute to False.

If thread use is disabled, transfer concurrency does not occur. Accordingly, the value of the max_request_concurrency attribute is ignored.

# Disable thread use/transfer concurrency
config = TransferConfig(use_threads=False)
manager = TransferManager(client, config)
manager.download_read_set(SEQUENCE_STORE_ID, "<my-read-set-id>")

Using the Omics URI Parser

Basic Usage

The OmicsUriParser class makes it easy to parse omics readset and reference URIs to extract fields relevant for calling AWS omics APIs.

Readset file URI:

Readset file URIs come in the following format:

omics://<AWS_ACCOUNT_ID>.storage.<AWS_REGION>.amazonaws.com/<SEQUENCE_STORE_ID>/readSet/<READSET_ID>/<SOURCE1/SOURCE2>

For example:

omics://123412341234.storage.us-east-1.amazonaws.com/5432154321/readSet/5346184667/source1
omics://123412341234.storage.us-east-1.amazonaws.com/5432154321/readSet/5346184667/source2

Reference file URI:

Reference file URIs come in the following format:

omics://<AWS_ACCOUNT_ID>.storage.<AWS_REGION>.amazonaws.com/<REFERENCE_STORE_ID>/reference/<REFERENCE_ID>/source

For example:

omics://123412341234.storage.us-east-1.amazonaws.com/5432154321/reference/5346184667/source

import boto3
from omics.uriparse.uri_parse import OmicsUriParser, OmicsUri

READSET_URI_STRING = "omics://123412341234.storage.us-east-1.amazonaws.com/5432154321/readSet/5346184667/source1"
REFERENCE_URI_STRING = "omics://123412341234.storage.us-east-1.amazonaws.com/5432154321/reference/5346184667/source"

client = boto3.client("omics")

readset = OmicsUriParser(READSET_URI_STRING).parse()
reference = OmicsUriParser(REFERENCE_URI_STRING).parse()

# use the parsed fields from the URIs to call omics APIs:

manager = TransferManager(client)

# Download all files for a reference.
manager.download_reference(reference.store_id, reference.resource_id)

# Download all files for a read set to a custom directory.
manager.download_read_set(readset.store_id, readset.resource_id, readset.file_name)

# Download a specific read set file with a custom filename.
manager.download_read_set_file(
    readset.store_id,
    readset.resource_id,
    readset.file_name,
    "my-sequence-data/read-set-index"
)

Using the Omics Rerun tool

Basic Usage

The omics-rerun tool makes it easy to start a new run execution from a CloudWatch Logs manifest.

List runs from manifest

The following example lists all workflow run ids which were completed on July 1st (UTC time):

> omics-rerun -s 2023-07-01T00:00:00 -e 2023-07-02T00:00:00
1234567 (2023-07-01T12:00:00.000)
2345678 (2023-07-01T13:00:00.000)

Rerun a previously-executed run

To rerun a previously-executed run, specify the run id you would like to rerun:

> omics-rerun 1234567
StartRun request:
{
  "workflowId": "4974161",
  "workflowType": "READY2RUN",
  "roleArn": "arn:aws:iam::123412341234:role/MyRole",
  "parameters": {
    "inputFASTQ_2": "s3://omics-us-west-2/sample-inputs/4974161/HG002-NA24385-pFDA_S2_L002_R2_001-5x.fastq.gz",
    "inputFASTQ_1": "s3://omics-us-west-2/sample-inputs/4974161/HG002-NA24385-pFDA_S2_L002_R1_001-5x.fastq.gz"
  },
  "outputUri": "s3://my-bucket/my-path"
}
StartRun response:
{
  "arn": "arn:aws:omics:us-west-2:123412341234:run/3456789",
  "id": "3456789",
  "status": "PENDING",
  "tags": {}
}

It is possible to override a request parameter from the original run. The following example tags the new run, which is particularly useful as tags are not propagated from the original run.

> omics-rerun 1234567 --tag=myKey=myValue
StartRun request:
{
  "workflowId": "4974161",
  "workflowType": "READY2RUN",
  "roleArn": "arn:aws:iam::123412341234:role/MyRole",
  "parameters": {
    "inputFASTQ_2": "s3://omics-us-west-2/sample-inputs/4974161/HG002-NA24385-pFDA_S2_L002_R2_001-5x.fastq.gz",
    "inputFASTQ_1": "s3://omics-us-west-2/sample-inputs/4974161/HG002-NA24385-pFDA_S2_L002_R1_001-5x.fastq.gz"
  },
  "outputUri": "s3://my-bucket/my-path",
  "tags": {
    "myKey": "myValue"
  }
}
StartRun response:
{
  "arn": "arn:aws:omics:us-west-2:123412341234:run/4567890",
  "id": "4567890",
  "status": "PENDING",
  "tags": {
    "myKey": "myValue"
  }
}

Before submitting a rerun request, it is possible to dry-run to view the new StartRun request:

> omics-rerun -d 1234567
StartRun request:
{
  "workflowId": "4974161",
  "workflowType": "READY2RUN",
  "roleArn": "arn:aws:iam::123412341234:role/MyRole",
  "parameters": {
    "inputFASTQ_2": "s3://omics-us-west-2/sample-inputs/4974161/HG002-NA24385-pFDA_S2_L002_R2_001-5x.fastq.gz",
    "inputFASTQ_1": "s3://omics-us-west-2/sample-inputs/4974161/HG002-NA24385-pFDA_S2_L002_R1_001-5x.fastq.gz"
  },
  "outputUri": "s3://my-bucket/my-path"
}

Security

See CONTRIBUTING for more information.

License

This project is licensed under the Apache-2.0 License.