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Causal Configuration

Definition
AI-generated

A causal configuration is a specific assignment of which variants in a locus are treated as causal (versus non-causal) within a fine-mapping model.

Topics
Population genetics Bayesian statistics
Related
Model Space Credible Set FINEMAP

Why it matters in GWAS

When many SNPs tag the same association because of LD, reasoning in terms of configurations clarifies what Bayesian fine-mapping actually estimates—often not a single “winner” SNP but posterior mass over multi-SNP explanations consistent with the data.

Example usage

"Fine-mapping compared one causal configuration at a time to estimate which variant sets best explained the locus."

Model Space Credible Set FINEMAP Fine-Mapping Linkage Disequilibrium (LD) Posterior Inclusion Probability (PIP)
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

  • Benner C, et al. (2016). FINEMAP: efficient variable selection using summary data from genome-wide association studies. Bioinformatics.
  • 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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