# Google BigQuery

To support more complex queries and advanced informatics workflows that use Google Cloud services, the Open Targets Platform data is also available as a Google Cloud public dataset via our Google BigQuery instance — [open-targets-prod](https://console.cloud.google.com/bigquery?p=open-targets-prod\&d=platform_21_06).

## What is Google BigQuery?

Google BigQuery is a data warehouse that enables researchers to run super-fast, asynchronous SQL queries using Google's cloud infrastructure. After running your query, you can either export into various formats or copy into a Google Cloud bucket for further downstream analyses.

Open Targets Platform data is publicly accessible as a [Google Cloud public dataset](https://console.cloud.google.com/marketplace/product/bigquery-public-data/open-targets-platform?project=open-targets-genetics). Users only pay for the queries they perform on the data, and through this program, the first 1 TB per month is free.

## BigQuery access points

Open Targets has uploaded all of our data to Google BigQuery. You can run queries via:

* [Cloud Console](https://cloud.google.com/bigquery/docs/quickstarts/quickstart-web-ui)
* [Command line `bq` tool](https://cloud.google.com/bigquery/docs/quickstarts/quickstart-command-line)
* [Client libraries, including Python](https://cloud.google.com/bigquery/docs/quickstarts/quickstart-client-libraries)

For more information on BiqQuery, please review the [BigQuery documentation](https://cloud.google.com/bigquery/docs).

## Example BigQuery SQL queries

Below is a sample query that uses our `association_overall_direct` dataset to return a list of targets associated with psoriasis (EFO\_0000676) and the overall association score.

```sql
SELECT
  associations.targetId AS target_id,
  targets.approvedSymbol AS target_approved_symbol,
  associations.diseaseId AS disease_id,
  diseases.name AS disease_name,
  associations.score AS overall_association_score
FROM
  `open-targets-prod.platform.association_overall_direct` AS associations
JOIN
  `open-targets-prod.platform.disease` AS diseases
ON
  associations.diseaseId = diseases.id
JOIN
  `open-targets-prod.platform.target` AS targets
ON
  associations.targetId = targets.id
WHERE
  associations.diseaseId='EFO_0000676'
ORDER BY
  associations.score DESC
```

Similarly, you can use our `drug_molecule` dataset and pass a list of drug trade names to find relevant information:

```sql
DECLARE
  my_drug_list ARRAY<STRING>;
SET
  my_drug_list = [ 'Premarin',
  'Calcium disodium versenate',
  'Keytruda',
  'Vioxx',
  'Humira' ];
SELECT
  id AS drug_id,
  name AS drug_chembl_name,
  tradeNameList.element AS drug_trade_name,
  drugType AS drug_type,
  isApproved AS drug_is_approved,
  blackBoxWarning AS drug_blackbox_warning,
  hasBeenWithdrawn AS drug_withdrawn,
FROM
  `open-targets-prod.platform.drug_molecule`,
  UNNEST (tradeNames.list) AS tradeNameList
WHERE
  (tradeNameList.element) IN UNNEST(my_drug_list)
```

## Tutorials and how-to guides

For more information on how to use BigQuery to access Platform data and example queries based on actual use cases and research questions, check out the [Open Targets Community](https://community.opentargets.org) and [our Google Cloud dataset homepage](https://console.cloud.google.com/marketplace/product/bigquery-public-data/open-targets-platform?project=open-targets-prod).&#x20;


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://platform-docs.opentargets.org/data-access/google-bigquery.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.