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Sum of Single Effects Model (SuSiE)

Definition
AI-generated

SuSiE is a sparse multiple-regression approach for genetic fine-mapping that represents association signal at a locus as a sum of a small number of single-SNP effects (“single effects”), each with its own pattern of linkage disequilibrium.

Topics
Population genetics
Synonyms
Sum of single effects
Related
Credible Set Posterior Inclusion Probability (PIP) FINEMAP

Why it matters in GWAS

SuSiE and its extensions (e.g. SuSiE-R for summary statistics, multi-trait and multi-ancestry variants) are standard tools for narrowing candidate causal variants when many SNPs are in LD, with interpretable Bayesian-style outputs.

Example usage

"We ran SuSiE on the region with LD from UK Biobank Europeans and obtained two non-overlapping 95% credible sets."

Credible Set Posterior Inclusion Probability (PIP) FINEMAP Fine-Mapping Fine-Mapping from Summary Statistics Functional Fine-Mapping Joint Fine-Mapping Multi-Ancestry Fine-Mapping SuSiE-inf Linkage Disequilibrium (LD)
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

  • Wang G, Sarkar A, Carbonetto P, Stephens M. (2020). A simple new approach to variable selection in regression, with application to genetic fine mapping. J R Stat Soc B.
  • Zou Y, Carbonetto P, Wang G, Stephens M. (2022). Fine-mapping from summary data with the “Sum of Single Effects” model. PLoS Genet.
  • Li Z, Zhou X. (2025). Towards improved fine-mapping of candidate causal variants. Nat Rev Genet. https://doi.org/10.1038/s41576-025-00869-4
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