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Statistical Genetics

Definition
AI-generated

Statistical genetics applies probability models and inference to related individuals and populations: heritability estimation, association mapping, polygenic prediction, and control of confounding from relatedness and population structure.

Topics
Core genetics
Related
Bioinformatics Genetic Relationship Matrix (GRM) Genome-Wide Association Study (GWAS)

Why it matters in GWAS

Core GWAS methods—mixed models for structure, multiple-testing control, fine-mapping posteriors, and PRS—are statistical genetics techniques whose assumptions determine valid discovery and generalization.

Example usage

"The analysis uses Statistical Genetics to quantify associations and compare alternative hypotheses."

Bioinformatics Genetic Relationship Matrix (GRM) Genome-Wide Association Study (GWAS) Heritability Linear Mixed Model (LMM) Multiple Testing Correction Polygenic Risk Score (PRS)
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. (2017). Concepts, estimation and interpretation of SNP-based heritability. 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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