Principled measures and estimates of trait polygenicity
O'Connor, L. J.; Sella, G.
Show abstract
The polygenicity of traits is often invoked and sometimes quantified in quantitative, statistical, and human genetics. What do we mean by the polygenicity of a trait? We propose a principled definition that encompasses a range of polygenicity measures. We show that these measures satisfy certain mathematical properties, we argue that these properties are sensible if not necessary, and we show that, conversely, measures that satisfy these properties also satisfy our definition. We consider four specific measures in greater detail, describe how they differ and show that three of them can be estimated from GWAS summary statistics using an existing method, Fourier Mixture Regression. We estimate these measures for 36 traits in humans. We find a dearth of traits with polygenicity values that fall within the large gap between Mendelian and highly polygenic traits. We discuss the evolutionary and cellular processes underlying trait polygenicity.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Hidden structure in polygenic scores and the challenge of disentangling ancestry interactions in admixed populations 96%
- Testing for differences in polygenic scores in the presence of confounding 95%
- A quantitative genetic model for indirect genetic effects and genomic imprinting under random and assortative mating 94%
Similar papers in this journal
- Predicting the direction of phenotypic difference 95%
- Trade-off between reducing mutational accumulation and increasing commitment to differentiation determines tissue organization 95%
- Testing and controlling for horizontal pleiotropy with the probabilistic Mendelian randomization in transcriptome-wide association studies 94%
Similar papers in this journal
- Polygenic score accuracy in ancient samples: quantifying the effects of allelic turnover 96%
- Beyond SNP Heritability: Polygenicity and Discoverability of Phenotypes Estimated with a Univariate Gaussian Mixture Model 95%
- Beyond SNP Heritability: Polygenicity and Discoverability of Phenotypes Estimated with a Univariate Gaussian Mixture Model 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.