Update of AstraZeneca PheWAS Portal

Shicheng_Guo · 16 May 2024 21:24

Hi Team,

It looks AstraZeneca PheWAS Portal have some update on latest UKB-WGS data result. Is there any roadmap/timeline opentarget to engage this update?

https://azphewas.com/phenotypeCatalogue

Thanks

Shicheng

irene · 17 May 2024 07:42

Hi @Shicheng_Guo,

we plan to update the AZ PheWAS Portal in our next release. We are tracking this effort in this issue, in case you’re interested.

github.com/opentargets/issues

Ingest AZ Phewas 470k burden results

opened 11:42AM - 03 May 24 UTC

ireneisdoomed

Data Platform

The associations from burden results in the AZ Phewas Portal were updated end of… last year. The update aggregates the ExWAS results from a cohort of 450k to **470k** people. We want to ingest this ## Background The raw data are several compressed CSVs that we can download from the [CGR Portal](https://az.app.box.com/v/azphewas-com/folder/233621623132) I've converted it to Parquet files: - Results from binary phenotypes: `gs://otar000-evidence_input/GeneBurden/data_files/azphewas-com-470k-phewas-binary` - Results from quantitative phenotypes: `gs://otar000-evidence_input/GeneBurden/data_files/azphewas-com-470k-phewas-quantitative` - Results from proteomics measurements (burden on PPP): `gs://otar000-evidence_input/GeneBurden/data_files/azphewas-com-470k-phewas-proteomics` ## Comparison between 470k and 450k results Our evidence consists overall consists of filtering the burden results to keep: 1) associations below the 1E-7 threshold, 2) associations that involve non synonymous variants. I've generated the evidence for the new data and compared to the previous one (currently in production). New evidence is here `gs://ot-team/irene/az_470k_evd` | | 450k | 470k | |---------------------------|---------|---------| | # evidence | 18129 | 28444 | | # unique target/phenotype | 5592 | 9004 | | mean p Value | 7.87E-9 | 7.58E-9 | | # unique phenotypes | 1473 | 2015 | | # binary phenotypes | 970 | 1156 | | # quantitative phenotypes | 502 | 856 | | # union phenotypes | 2939 | 3745 | I think this shows that now we are able to find statistically significance differences thanks to the greater sample size. This means that we could potential have a very substantial gain of 60% more associations. ## Sorting out phenotype mapping The gain in new associations mean that we have a bigger coverage in traits, which we have to map. On top of that, I've also realised that many of the phenotype descriptions have changed between cohorts: - 97% of the 470k associations are not found in the 450k set (potentially new) - 96% of the 450k associations are not found in the 470k set (potentially lost) This just means that although the disease is the same between cohorts, its description has changed. This is annoying because we map traits by name using [this table](https://github.com/opentargets/curation/blob/master/mappings/disease/manual_string.tsv). An example: - LDLR is associated with `41202#I25#I25 Chronic ischaemic heart disease` in the 450k set - LDLR is associated with `41202#I25#Chronic ischaemic heart disease` in the 470k set (note the second I25 is missing) Union phenotypes also have different descriptions: 450k says `Union`, 470 says `union`. This is simple to address. ## Tasks The biggest problem of ingesting the new data is mapping the new traits. The data model has not changed, so once it is sorted ingesting it will be easy. In following comments I'll describe what we can do about it, and some comments about the proteomics set, which I don't think is in scope for this release.

Have a nice day!
Irene

Shicheng_Guo · 10 June 2024 23:03

AZ phewas portal has a Burden test P-value cut-off as 0.0044. I am wondering if OpenTarget could remove this filtering and show the full result?

Thanks.

Shicheng

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Update of AstraZeneca PheWAS Portal

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