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Infinitesimal-Background Fine-Mapping (SuSiE-inf)

Definition
AI-generated

SuSiE-inf extends SuSiE by jointly modeling a sparse set of large causal effects at a locus with a polygenic (infinitesimal) background contribution from many small effects across the region—related in spirit to BSLMM.

Topics
Population genetics
Related
Credible Set Fine-Mapping SNP Heritability

Why it matters in GWAS

Standard sparse fine-mappers can misbehave when signal is not purely a few large effects; SuSiE-inf targets loci where heritability is spread across many SNPs yet a subset may still be prioritized for follow-up.

Example usage

"We ran SuSiE-inf when the locus showed broad signal on regional heritability plots but SuSiE returned unstable credible sets."

Credible Set Fine-Mapping SNP Heritability SuSiE
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

  • Cui R, et al. (2024). Improving fine-mapping by modeling infinitesimal effects. Nat Genet.
  • Zhou X, Carbonetto P, Stephens M. (2013). Polygenic modeling with Bayesian sparse linear mixed models. 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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