# Public Results Using the developed PennPRS pipelines, we are conducting single-ancestry and multi-ancestry PennPRS pseudo training for publicly available GWAS summary statistics and have made these PRS weights publicly available in the PennPRS resource hub ("[Public Results](https://pennprs.org/result)"). These resources will accelerate the application of PRS across various fields. As the GWAS Catalog and other databases continue to expand and harmonize GWAS summary statistics, we will keep analyzing additional datasets to better serve the research community. ### GWAS Catalog harmonized datasets We are performing single-ancestry PRS analysis for harmonized datasets in the GWAS Catalog. To date, we have generated PRS weights for over 8000 single-ancestry datasets from the[ GWAS Catalog](https://pennprs.org/data). We use the [pseudo PRS training mechanism](https://pennprs.gitbook.io/pennprs/pages/f3qgt8LxfeMyvNylat7m#option-1.-pseudo-prs-training-by-using-summary-data-for-parameter-tuning), select all three currently supported methods (C+T, LDpred2, and Lassosum2) with the default parameter setting, and also run their ensemble. All these PRS weights are freely available for users to download.

Publicly available PRS weights for GWAS Catalog harmonized datasets.

### MVP study We are performing multi-ancestry analysis for phenotypes in the Million Veteran Program ([MVP](https://www.science.org/doi/10.1126/science.adj1182)) study. To date, we have generated PRS weights for 181 phenotypes that have GWAS summary statistics from four populations: AFR, AMR, EAS, and EUR. We use the pseudo-training version of [PROSPER](https://www.nature.com/articles/s41467-024-47357-7) with the default parameter setting. All these PRS weights are freely available for users to download.

Publicly available PRS weights for MVP datasets.

### Biobank Japan We are performing single-ancestry PRS analysis for GWAS datasets in [Biobank Japan](https://biobankjp.org/en/). To date, we have generated PRS weights for 169 single-ancestry datasets from [Biobank Japan](https://pheweb.jp/downloads). We use the [pseudo PRS training mechanism](https://pennprs.gitbook.io/pennprs/pages/f3qgt8LxfeMyvNylat7m#option-1.-pseudo-prs-training-by-using-summary-data-for-parameter-tuning), select all three currently supported methods (C+T, LDpred2, and Lassosum2) with the default parameter setting, and also run their ensemble. All these PRS weights are freely available for users to download.

Publicly available PRS weights for Biobank Japan datasets.

### GBMI We are performing multi-ancestry analysis for phenotypes from the Global Biobank Meta-analysis Initiative ([GBMI](https://www.cell.com/consortium/global-biobank-meta-analysis-initiative)) consortium. To date, we have generated PRS weights for 9 diseases that have [GWAS summary statistics](https://www.globalbiobankmeta.org/resources) from at least two populations from AFR, AMR, EAS, SAS, and EUR. We use the pseudo-training version of [PROSPER](https://www.nature.com/articles/s41467-024-47357-7) with the default parameter setting. All these PRS weights are freely available for users to download.

Publicly available PRS weights for GBMI datasets.

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