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Lassosum

Definition
AI-generated

Lassosum fits polygenic scores by applying penalized regression (lasso-style shrinkage) to GWAS summary statistics while accounting for linkage disequilibrium via a reference panel, producing sparse or dense weight sets depending on the penalty.

Topics
Post-GWAS
URL
https://github.com/tshmak/lassosum
Related
GWAS Summary Statistics LDpred Linkage Disequilibrium (LD)

Why it matters in GWAS

It offers a summary-statistic–based PRS method that can adaptively down-weight noisy effects and is used alongside PRSice-style and Bayesian approaches in method comparisons.

Example usage

"We generated lassosum weights in the ancestry-matched reference LD panel and evaluated R² in the target sample."

GWAS Summary Statistics LDpred 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

  • Mak TSH, et al. (2017). Polygenic scores via penalized regression on summary statistics. Genet Epidemiol.
  • 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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