import os
import tiledb
# You should set the appropriate environment variables with your keys.
# Get the keys from the environment variables.
tiledb_account = os.environ["TILEDB_ACCOUNT"]
tiledb_token = os.environ["TILEDB_REST_TOKEN"]
# or use your username and password (not recommended)
# tiledb_username = os.environ["TILEDB_USERNAME"]
# tiledb_password = os.environ["TILEDB_PASSWORD"]
# Get the bucket and region from environment variables
s3_bucket = os.environ["S3_BUCKET"]
# Set the AWS keys and region to the config of the default context
# This context initialization can be performed only once.
cfg = tiledb.Config(
{
"vfs.s3.no_sign_request": "true", # boosts performance when accessing public S3 buckets
"rest.token": tiledb_token,
# or use your username and password (not recommended)
# "rest.username": tiledb_username,
# "rest.password": tiledb_password,
}
)
ctx = tiledb.Ctx(cfg)Basic TileDB Cloud
life sciences
genomics (vcf)
tutorials
remote access
Demonstration of basic usage of TileDB-VCF on TileDB Cloud.
How to run this tutorial
You can run this tutorial only on TileDB Cloud. However, TileDB Cloud has a free tier. We strongly recommend that you sign up and run everything there, as that requires no installations or deployment.
This tutorial shows basic usage of TileDB-VCF on TileDB Cloud. It assumes you have already completed the Get Started section.
Start by setting some environment variables. It can look something like this:
import os
os.environ["S3_BUCKET"] = "s3://<your_bucket_name>"
os.environ["TILEDB_ACCOUNT"] = "<your_tiledb_account_username>"Next, fetch the environment variables you created and define the global context:
The rest of the tutorial is very similar to the Tutorials: Basic Ingestion section, whereas you can create, write, and read any VCF dataset in the same manner after setting up your TileDB credentials as shown above.
First, import the necessary libraries, set the TileDB-VCF dataset URI (i.e., its path, which in this tutorial will be on local storage), and delete any previously created datasets with the same name.
Specify the VCF samples you would like to ingest.
Next, create the TileDB-VCF dataset and ingest the specified samples. The only difference between TileDB Cloud and TileDB-VCF open-source when creating datasets is that the TileDB Cloud URI should be of the form: tiledb://<account>/s3://<bucket>/<vcf_dataset>. TileDB Cloud understands that you are trying to create a VCF dataset in S3 URI s3://<bucket>/<vcf_dataset> and register it under <account>. After you create the dataset, you can access the array as tiledb://<account>/<vcf_dataset>.
Warning
The following block may take a lot of time if you are running it from your local machine with poor internet connection. For best performance, it is highly recommended that you run it from a TileDB Cloud notebook.
Read some data using TileDB-VCF. Again, you access the array with URI tiledb://<account>/<vcf_dataset>.
Clean up in the end by deleting the dataset. This command will unregister the VCF dataset from TileDB Cloud and physically delete all groups and arrays comprising the dataset from the physical storage.