# Methods for Human Genetic Mapping

> **NIH NIH R01** · UNIVERSITY OF CHICAGO · 2020 · $449,283

## Abstract

Project Summary/Abstract
Common, complex diseases together account for a large portion of the health care burden in the United States, and
genetic analysis of these traits remains one of the major challenges facing biomedical researchers. Advances in high-
throughput technologies have led to increasing availability of large-scale genetic sequence information and other related
biological data sets. If robust, powerful statistical and computational methods and tools are developed to analyze these
data, then additional progress can be made on identifying and characterizing the genetic components of complex
disorders. This, in turn, has the potential to (1) lead to better understanding of the biology of such disorders, (2) clarify
the role of environmental risk factors, which could be targets of cost-effective treatment and prevention strategies, and
(3) lead to improvements in personalized medical care. The goal of the project is development of robust, powerful
trait-association data analysis methods that will be useful for a wide variety of complex traits in a full spectrum of study
designs, including unrelated samples with mild population structure, samples of related individuals, and individuals
from admixed or founder populations. Specific aims of the project are development of (1) more powerful association
methods for binary traits, including joint analysis of multiple phenotypes and multiple genetic variants; (2) fast, robust
methods for assessing significance in a wide variety of association studies, including methods to detect sparse and
weak association signals; and (3) methods to analyze genetic interaction in an association analysis, for one genome
or a pair of interacting genomes. The proposed methods incorporate relevant covariates, allow ascertainment, and
account for population structure and relatedness of individuals in the sample. Together, the insights attained from
the proposed methods and their application to current genetic questions will drive further discoveries into and create
greater understanding of the genetics of complex traits.
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## Key facts

- **NIH application ID:** 9986857
- **Project number:** 5R01HG001645-21
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** MARY SARA MCPEEK
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $449,283
- **Award type:** 5
- **Project period:** 1997-09-01 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9986857

## Citation

> US National Institutes of Health, RePORTER application 9986857, Methods for Human Genetic Mapping (5R01HG001645-21). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9986857. Licensed CC0.

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