ID mapping table

Data Access
,
1

Hi All,

Recently I’ve been interested in having a reference table for mapping ENSEMBL gene ids to HGNC symbols. I thought that i could get that information by dowloading the Targets data from OT (Index of /pub/databases/opentargets/platform/23.09/output/etl/parquet/targets). However, after downloading and Parsing the parquet files I only find ~ 1000 unique ENSEMBL gene ids. In contrast, I’ve used a similar approach to also download and parse the OT - DepMap data (Index of /pub/databases/opentargets/platform/23.09/output/etl/parquet/targetEssentiality) , and in that case I do find ~ 17000 unique ENSEMBL ids.

Is it possible to download from OT a set of id mapping data/parquets for all genes in the human genome ?

Kind regards ,

-Mathias

2

Hi Mathias,

I suspect you need to double check your local files that you have retrieved from ftp. I have just tried the target index from the September release and it has 62.7k unique ids.

Best,
Daniel

3

You need to download the whole directory and read all the partitions at once (no need for for loops. Each individual file on this directory is just a chunk of the data (used for parallelised computing).

You might also benefit from looking at the searchTarget[Index of /pub/databases/opentargets/platform/23.09/output/etl/parquet/searchTarget] dataset. This dataset feeds the Open Targets Platform search, but it contains a lookup with all the alternative IDs we use for every target. The data is derived from the target dataset, so it’s basically the same information but it might be in a friendlier format if you want to build mappings beyond the approveSymbol.

In our upcoming release there will also be a graphQL API endpoint to perform the same task:

4

Thanks for your advice. I figured that the error was happening for the following reason: I used read_parquet() from the ‘arrow’ parquet to read the parquet files. arrow::read_parquet( ) reads the parquet files into a tibble. I then used unnest() from tidyr to expand the list-columns . Apparently, some entries in this list columns might be NULL or NA. If so, when using unnest(), this entries will get dropped. To fix this behavior one must specify ‘keep_empty = TRUE’ inside unnest.

Blockquote

1 Like