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Conditional Association Analysis

Definition
AI-generated

Conditional association analysis tests whether a variant remains associated with a trait after accounting for genotype at one or more other variants—usually the lead SNP(s) in the same locus—so secondary signals can be distinguished from a single shared haplotype effect.

Topics
GWAS
Related
Fine-Mapping Genome-Wide Association Study (GWAS) GWAS Summary Statistics

Why it matters in GWAS

Many loci contain multiple independent signals; conditioning reveals distinct association peaks for fine-mapping, functional follow-up, and cleaner summary statistics for PRS or colocalization.

Example usage

"Conditional association analysis revealed a secondary signal after adjusting for the lead SNP at the locus."

Fine-Mapping Genome-Wide Association Study (GWAS) GWAS Summary Statistics Linkage Disequilibrium (LD) Single Nucleotide Polymorphism (SNP) Winner's Curse
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

  • Yang J, et al. (2012). Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat Genet.
  • Uffelmann E, et al. (2021). Genome-wide association studies. Nat Rev Methods Primers. https://doi.org/10.1038/s43586-021-00056-9
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