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Pleiotropy Dissection

Definition
AI-generated

Pleiotropy dissection refers to analytical approaches that partition or explain how a variant or locus influences multiple traits—for example by distinguishing mediation through one trait versus independent effects, joint modeling of traits, or integrating functional and multi-omic data.

Topics
Post-GWAS
Related
Colocalization Conditional Association Analysis Fine-Mapping

Why it matters in GWAS

Without dissection, overlapping associations can be misread as simple shared causation; explicit models and multi-trait methods clarify biological versus statistical overlap and support target prioritization.

Example usage

"Downstream interpretation uses Pleiotropy Dissection to connect statistical signals with biological context."

Colocalization Conditional Association Analysis Fine-Mapping Genomic Structural Equation Modeling (Genomic SEM) Joint Fine-Mapping Matrix Factorization for Pleiotropy Mendelian Randomization (MR) Multi-Trait GWAS Pleiotropy Vertical Pleiotropy
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

  • Jee J, et al. (2026). The pleiotropic landscape of the human genome. Nat Rev Genet. https://doi.org/10.1038/s41576-025-00908-0
← Pleiotropy PLINK →

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