Authors: Davide Piffer
Polygenic scores (PGS) are being used to predict group-level traits across time and space, hence proving useful to detect recent selection. The aim of this study is to investigate the impact of different p value thresholds on signal to noise ratio and predictive validity of polygenic scores, using the largest GWAS of educational attainment and cognition to date. Signal to noise ratio linearly decreases with p value, but this phenomenon is limited to Eurasians. There is a linear degradation of validity and population differentiation in allele frequencies with higher p values. However, compounded polygenic scores have a quadratic relationship with p value. A thresholding at or below the conventional GWAS significance (p<5*10-8) seems to maximize validity, corroborating earlier results. The highest correlation with population IQ is achieved by the Highest Math Class completed and the EDU MTAG PGS (r= 0.90 and 0.89, respectively). Using random SNPs, it is shown that correlations of this magnitude occur only once out of 46k trials. A table provides an empirical estimate of the rarity of the correlation coefficients and it is shown that they are a function of PGS size. Finally, an analogy between the noise contained in polygenic scores and physical instruments is put forward.
Comments: 16 Pages.
[v1] 2019-07-05 15:22:57
Unique-IP document downloads: 61 times
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