At Open Targets, we have several ways of accessing our data. In this post, we illustrate how to make the best use of it from the BigQuery workspace.
This query is an example of how to extract the drugs that are on the market for a restricted list of targets.
SELECT targets.approvedSymbol, targets.id, ARRAY_AGG(drugs.id) AS drugIds FROM `open-targets-prod.platform_21_04.molecule` AS drugs, UNNEST(linkedTargets.rows.list) AS linkedTarget JOIN `open-targets-prod.platform_21_04.targets` AS targets ON targets.id = linkedTarget.element WHERE drugs.maximumClinicalTrialPhase = 4 AND targets.approvedSymbol IN ( 'ERBB3', 'EGFR' ) GROUP BY targets.id, targets.approvedSymbol
This is an alternative to the batch search functionality of the previous version so that we allow our users to have more control and to elaborate more complex hypotheses with the vast amount of data available in the Platform.
If the query becomes more complex or the set of targets is very large, we encourage you to see how these same steps would be done using our data downloads in this post.
Confused? Let’s break it down:
We use 2 datasets to establish the relationship between the drug and the target:
- Target, which contains the HGNC Symbols;
- Molecule, with the annotation of the drug molecules.
The molecule dataset comprises in
linkedTargets.rows all the targets (in the form of Ensembl gene IDs) on which a drug acts according to its mechanism of action.
When joining the two tables, the only thing we have to take into account is that this field is an array that we have to flatten with
UNNEST to establish the pairwise relationship between each array element and the id from target.
We want to filter out drugs with a maximum phase observed in clinical trials below < 4 to perform the analysis only on those drugs that are available on the market.
Grouping first by the symbol and the ENSID of the target, we collect all the resulting drugs in the array
Both the query and our datasets are publicly available at this link.
To download the results simply click
Run > Save Results under the Query results section.
Consult the BigQuery documentation if you have problems accessing the workspace.