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LDpred

Definition
AI-generated

LDpred is a Bayesian framework that constructs polygenic scores from GWAS summary statistics by modeling linkage disequilibrium (with an external LD reference) and applying shrinkage of SNP effect estimates, aiming to improve prediction over simple *P*-value thresholding when the architecture is polygenic.

Topics
Post-GWAS
URL
https://github.com/bvilhjal/ldpred
Related
GWAS Summary Statistics Lassosum Linkage Disequilibrium (LD)

Why it matters in GWAS

It is a standard alternative to clumping-and-thresholding for summary-statistic–based PRS, especially when large discovery samples and appropriate LD panels are available.

Example usage

"LDpred structure informed clumping, fine-mapping, and interpretation of nearby association peaks."

GWAS Summary Statistics Lassosum Linkage Disequilibrium (LD) Polygenic Risk Score (PRS) PRS Base Cohort PRS Clumping and Thresholding PRS Target Cohort PRSice-2
Related-term network

Click any node to open that term page.

Node order. The current term is first. Next come every page linked from Related terms, in the same top-to-bottom order as that list. Then new terms appear in two-hop layers: for each of those direct neighbors (in that same order), their related terms are appended if not already listed. A third pass does the same for two-hop nodes. The walk stops when a fixed maximum number of nodes is reached.

References

  • Vilhjálmsson BJ, et al. (2015). Modeling linkage disequilibrium increases accuracy of polygenic risk scores. Am J Hum Genet.
  • Choi SW, Mak TSH, O'Reilly PF. (2020). Tutorial: a guide to performing polygenic risk score analyses. Nat Protoc. https://doi.org/10.1038/s41596-020-0353-1
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