Estimating genetic correlation jointly using individual-level and summary-level GWAS data
Yiliang Zhang, Wei Jiang, Jiangnan Shen, Youshu Cheng, Yixuan Ye, Qiongshi Lu, Hongyu Zhao · 2026
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Description
Yiliang Zhang and co-authors present a method to estimate how alike two traits are genetically when the data come in mixed formats in a 2026 paper. Big gene studies release either full individual records or only summary tables, often one trait of each kind. Older methods need both traits in the same format, forcing wasteful conversions that lose information.
Their method works directly with one trait at the individual level and the other as summaries, within one population or across ancestries. In simulations and real data it gave more reliable and efficient estimates than summary-only routes. The team also show that sharper correlation estimates improve prediction of disease risk scores across populations.
Catalog record
| CREATOR | Yiliang Zhang, Wei Jiang, Jiangnan Shen, Youshu Cheng, Yixuan Ye, Qiongshi Lu, Hongyu Zhao |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 81 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |