# Accurately Inferring Demographic Histories of Human Populations Using Large Whole Genome Sequence Data

> **NIH NIH R01** · UNIVERSITY OF SOUTH FLORIDA · 2020 · $308,849

## Abstract

PROJECT SUMMARY
Inferring the demographic history of a population is an important task in population genetics.
Although several methods are available for this task, how to take advantage of large sample
size of whole genome sequence data and provide accurate estimation of demographic history
remains an open question. We propose several approaches to overcome the shortcomings of
existing methods and specifically improve their accuracy and scalability for large sample size
and whole genome sequence data. The resulting methods will be applied to the whole genome
sequences of the genotype-rich human populations such as the TOPMED European American
cohorts (~30,000 individuals) and Icelander whole genome sequence data (2,636 individuals),
and provide good estimation of the demographic histories. Finally, a software package will be
developed to incorporate the new methods and assist other researchers to easily apply the
method to their own data.

## Key facts

- **NIH application ID:** 9933971
- **Project number:** 5R01HG009524-05
- **Recipient organization:** UNIVERSITY OF SOUTH FLORIDA
- **Principal Investigator:** XIAOMING LIU
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $308,849
- **Award type:** 5
- **Project period:** 2018-08-30 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9933971

## Citation

> US National Institutes of Health, RePORTER application 9933971, Accurately Inferring Demographic Histories of Human Populations Using Large Whole Genome Sequence Data (5R01HG009524-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9933971. Licensed CC0.

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