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Fine-Mapping from Summary Statistics

Definition
AI-generated

Fine-mapping from summary statistics infers likely causal variants using per-SNP GWAS effect estimates and standard errors (or *Z*-scores) together with an LD correlation matrix from a reference panel, without individual-level genotypes.

Topics
Population genetics
Synonyms
Summary-statistics fine-mapping
Related
CARMA Fine-Mapping Credible Set FINEMAP

Why it matters in GWAS

Most public discoveries distribute only summary statistics; summary-based fine-mapping enables secondary analysis but requires careful matching of allele alignment, ancestry, and cohort heterogeneity—issues that can miscalibrate posteriors in meta-analysis (see SLALOM).

Example usage

"Downstream interpretation uses Fine-Mapping from Summary Statistics to contextualize the main association signal."

CARMA Fine-Mapping Credible Set FINEMAP Fine-Mapping GWAS Summary Statistics Linkage Disequilibrium (LD) SLALOM 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

  • Zou Y, Carbonetto P, Wang G, Stephens M. (2022). Fine-mapping from summary data with the “Sum of Single Effects” model. PLoS Genet.
  • Kanai M, et al. (2022). Meta-analysis fine-mapping is often miscalibrated at single-variant resolution. Cell Genom.
  • 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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