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Imputation Quality Metric

Definition
AI-generated

Imputation quality metrics summarize how confidently genotypes were inferred at each variant (e.g. MaCH/Minimac Rsq, IMPUTE-style INFO).

Topics
GWAS
Related
Call Rate Genotype Dosage Genotype Imputation

Why it matters in GWAS

Hard thresholds on quality metrics reduce noise and false positives from poorly imputed variants but can discard real signal if thresholds are arbitrary; reporting filters (e.g. INFO > 0.8 for common SNPs) is standard for reproducibility.

Example usage

"Imputation Quality Metric is referenced when translating statistical signals into biological context."

Call Rate Genotype Dosage Genotype Imputation Minor Allele Frequency (MAF) Quality Control (QC) Rare Variant
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

  • Sun Q, et al. (2022). MagicalRsq: machine-learning-based genotype imputation quality calibration. Am J Hum Genet.
  • Sun Q, Li Y. (2026). Advances in haplotype phasing and genotype imputation. Nat Rev Genet. https://doi.org/10.1038/s41576-025-00895-2
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