Data Download
You can get all data from Open Targets Genetics via:
​Google Cloud Storage (GCS) paywalled public bucket
Google BigQuery, project open-targets-genetics:190303
We will be making this data available on the Open Targets FTP. Please check again shortly.
Please refer to the Requester Pays feature for Google Cloud Storage.
Although Open Targets makes this data publicly available, all data charges for the bucket open-targets-genetics-releases will be billed to the requester.
Although we make Open Targets Genetics data publicly available, all charges to the bucket open-targets-genetics-releases will be billed to the requester.
Please refer to the Requester Pays feature for Google Cloud Storage for more detail.
Data | 19.03.03 |
​Backend scripts​ | 19.03.08 |
​Spark pipeline​ | 19.03.10 |
​GraphQL API​ | 19.03.11 |
The list of datasets with each corresponding data schema
Please change the URL tags to their corresponding tables, stated above, as required.
Folder name | Format | Spark Schema | SQL Schema (Clickhouse Dialect) |
variant-index | parquet | - | - |
v2g | jsonl | ​schema link​ | ​schema link​ |
v2d | jsonl | ​schema link​ | ​schema link​ |
d2v2g | jsonl | - | ​schema link​ |
lut/genes-index | jsonl | - | ​schema link​ |
lut/overlap-index | jsonl | - | ​schema link​ |
lut/study-index | jsonl | - | ​schema link​ |
lut/variant-index | jsonl | - | ​schema link​ |
You can potentially stream the content directly from a Google Cloud Bucket using gsutil command
gsutil cat 'gs://open-targets-genetics-releases/19.03.04/lut/variant-index/part-*' | head -1 | jq .{"chr_id": "1","position": 55545,"ref_allele": "C","alt_allele": "T","rs_id": "rs28396308","most_severe_consequence": "downstream_gene_variant","gene_id_any_distance": 13546,"gene_id_any": "ENSG00000186092","gene_id_prot_coding_distance": 13546,"gene_id_prot_coding": "ENSG00000186092","raw": 0.028059,"phred": 3.065,"gnomad_afr": 0.3264216148287779,"gnomad_amr": 0.4533582089552239,"gnomad_asj": 0.26666666666666666,"gnomad_eas": 0.35822021116138764,"gnomad_fin": 0.31313131313131315,"gnomad_nfe": 0.26266330506532204,"gnomad_nfe_est": 0.3397858319604613,"gnomad_nfe_nwe": 0.23609443777511005,"gnomad_nfe_onf": 0.2256,"gnomad_nfe_seu": 0.1,"gnomad_oth": 0.27403846153846156}
There is an initial bash script you can use in order to load all data into a ClickHouse instance. In that script, you will find lines like this
echo create studies tablesclickhouse-client -m -n < studies_log.sqlgsutil cat "${base_path}/lut/study-index/part-*" | clickhouse-client -h 127.0.0.1 --query="insert into ot.studies_log format JSONEachRow "clickhouse-client -m -n < studies.sqlclickhouse-client -m -n -q "drop table ot.studies_log;"
