# Methods to enable robust and efficient use of genetic summary data

> **NIH NIH R35** · UNIVERSITY OF COLORADO DENVER · 2020 · $431,352

## Abstract

Abstract
Publiclyavailable genetic summary data canhave high utility for providing insight into genetic etiology
of health and disease. Databases of genotype frequencies, such as the genome Aggregation Database
(gnomAD), are used to prioritize putative causal variants and, more recently, as pseudo-controls in
case-control analysis. Genome Wide Association Study (GWAS) test statistics are used in a variety of
secondary data analyses including polygenic risk scores (PRS), genetic correlation analysis, and fine
mapping of causal variants. Compared with individual level data, genetic summary data often has fewer
barriers in access, promoting broad use of these valuable data resources. The availability and use of
summary genetic data is often not equitable across all ancestral groups, especially for understudied
ancestral groups that have little to no representation within these resources. Furthermore,
heterogeneity within the summary data can lead to confounding and reduced power for case-control
analysis, incorrect prioritization of putative causal variants for rare diseases, and reduced accuracy for
polygenic risk scores. I develop robust and efficient methods to appropriately use genetic summary
data while estimating, modeling, and harnessing the heterogeneity within. My methods coalesce around
a unifying framework where I flip the paradigm of genetic and genomic data treating the genetic variant
or element as the observational unit by which we analyze the data rather than the individual. This
simple, yet innovative paradigm shift enables the use of classical statistical techniques and the creation
of methods that detect, adjust for, and even use heterogeneity within summary level data. To enable
broad and equitable use of our methods, we will create publicly available R packages compatible with
Bioconductor and Shiny Apps for interactive internet use.

## Key facts

- **NIH application ID:** 10047677
- **Project number:** 1R35HG011293-01
- **Recipient organization:** UNIVERSITY OF COLORADO DENVER
- **Principal Investigator:** Audrey E Hendricks
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $431,352
- **Award type:** 1
- **Project period:** 2020-09-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10047677

## Citation

> US National Institutes of Health, RePORTER application 10047677, Methods to enable robust and efficient use of genetic summary data (1R35HG011293-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10047677. Licensed CC0.

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