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A mathematical and summary statistics based framework for the analysis of polygenic risk score and large-effect variants

Authors: Zhou, Dan; Gamazon, Eric;

A mathematical and summary statistics based framework for the analysis of polygenic risk score and large-effect variants

Abstract

We provide a set of scripts for simulating, estimating, and visualizing the relationship between common, small effect variant Polygenic Burden (PB) and Large-Effect Variant (LEV). We present a mathematical and summary statistics based framework that utilizes the relationship between PB and LEV among cases for some methodologically-and clinically-relevant applications. Details can be found in our manuscript ‘Contextualizing genetic risk score for disease screening and rare variant discovery’. For questions on the software, please contact Eric R. Gamazon, PhD (at ericgamazon@gmail.com). Please cite: Dan Zhou, Dongmei Yu, Jeremiah M. Scharf, Carol A. Mathews, Lauren McGrath, Edwin Cook, S Hong Lee, Lea K. Davis§, Eric R. Gamazon§. Contextualizing genetic risk score for disease screening and rare variant discovery. Dan Zhou & Eric R. Gamazon. (2021). A mathematical and summary statistics based framework for the analysis of polygenic risk score and large-effect variants. Zenodo. https://zenodo.org/record/4767933

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Keywords

polygenic risk score, rare variants, GWAS, genetic architecture, disease liability, biobank, penetrance

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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