# Which TWAS Catalog Do You Recommend for Target Discovery?

**URL:** <https://community.opentargets.org/t/which-twas-catalog-do-you-recommend-for-target-discovery/2044>\
**Category:** General\
**Created:** [26 June 2026 04:36 UTC](https://community.opentargets.org/t/which-twas-catalog-do-you-recommend-for-target-discovery/2044 "2026-06-26T04:36:51Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![Shicheng\_Guo](https://dub1.discourse-cdn.com/flex017/user_avatar/community.opentargets.org/shicheng_guo/32/217_2.png) [@Shicheng\_Guo](https://community.opentargets.org/u/Shicheng_Guo)\
**Post date:** [26 June 2026 04:36 UTC](https://community.opentargets.org/t/which-twas-catalog-do-you-recommend-for-target-discovery/2044/1 "2026-06-26T04:36:51Z")

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I’m looking for community recommendations on **TWAS resources** for target discovery and prioritization.

There are now quite a few TWAS catalogs and atlases available (e.g., **GTEx/PrediXcan** , **TWAS Hub** , **Open Targets Genetics** , **eQTL Catalogue** , **GTEx v8/v9-based resources** , and various disease-specific TWAS databases), each differing in tissues, molecular models, sample size, ancestry, and statistical framework.

For those actively using TWAS in pharmaceutical target discovery:

- Which **TWAS catalog or atlas** do you rely on most?

- Which resource has the best coverage, quality, and ease of integration into target prioritization pipelines?

- Are there any community “gold standards” emerging for large-scale analyses?

- If you had to recommend a single resource (or a combination of resources) for systematic target discovery, what would it be, and why?

I’m particularly interested in resources that are well-maintained, regularly updated, and suitable for genome-wide, production-scale analyses.

Thanks in advance for sharing your experience and recommendations!

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**Author:** ![sourabh](https://avatars.discourse-cdn.com/v4/letter/s/9dc877/32.png) [@sourabh](https://community.opentargets.org/u/sourabh)\
**Post date:** [5 October 2026 09:04 UTC](https://community.opentargets.org/t/which-twas-catalog-do-you-recommend-for-target-discovery/2044/2 "2026-10-05T09:04:09Z")

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Not a daily TWAS user, so I’ll leave the “which one is best” to people who run them, but one thing from building target-prioritisation pipelines on top of these catalogs that I’d put ahead of the choice of resource:

Track what each catalog _didn’t test_, per gene, per tissue. A gene missing from a TWAS Hub or PhenomeXcan result set is almost always a gene with no expression model that cleared the prediction-r² threshold in that tissue — not a gene that was tested and came up null. If the pipeline treats both as “no association”, it silently penalises every gene with low cis-heritability, which is a lot of good targets. Same with ancestry: most GTEx-trained models are European-ancestry; a null in a non-European GWAS is often a transferability gap, not biology.

Practically, for each catalog I’d record three columns next to every gene–trait cell: model available (y/n, r²), tissues tested (count of N), and training ancestry. Then absences become “not in universe” versus “measured null”, and you can combine catalogs — e.g. GTEx v8 MASHR models via S-PrediXcan for breadth, eQTL Catalogue for harmonised per-study effects and colocalisation, Open Targets L2G as the gene-prioritisation layer rather than as a TWAS source — without the union quietly inheriting each one’s blind spots.

Beyond that: whatever you pick, pair it with colocalisation (coloc/SuSiE) before calling a gene, since TWAS hits share a locus with the causal gene more often than they are it; and check the resource’s last update date, because several of the precomputed atlases froze around 2020–2022.

Happy to share the per-gene coverage schema if useful.