# Joint inferences of natural selection between sites and populations

> **NIH NIH R01** · UNIVERSITY OF ARIZONA · 2020 · $199,665

## Abstract

Project Summary/Abstract
There is a critical need to improve the robustness and accessibility of computational approaches
in population genomics. The PI's long-term goals are to develop methods for inferring evolutionary
history from population genomic data and to support the scientific community in their use. The ob-
jectives of this supplement application are to bring his widely used software dadi to the cloud and
to improve its development and documentation. The rationale for the proposed development is that
dadi is computationally intensive and often used by empirical research groups with modest com-
putational resources, so bringing dadi to the cloud will dramatically increase these researchers'
access to sophisticated population genomic modeling.
In Aim 1, the PI proposes to collaborate with cloud computing experts to bring dadi to several
cloud environments, including those served by NIH STRIDES.
In Aim 2, the PI proposes to improve the development environment for dadi, through more com-
plete and automated testing.
In Aim 3, the PI proposes to improve the user environment for dadi, through improved documen-
tation and interoperability with standard file formats.
The expected outcome of the proposed supplement is a dramatically improved software tool for
inferring models of population history and natural selection from population genomic data. This
outcome is expected to positive impact on the field of population genomics, by increasing the
accessibility and robustness of the widely-used dadi software.
Project Summary/Abstract

## Key facts

- **NIH application ID:** 10166182
- **Project number:** 3R01GM127348-02S1
- **Recipient organization:** UNIVERSITY OF ARIZONA
- **Principal Investigator:** Ryan Gutenkunst
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $199,665
- **Award type:** 3
- **Project period:** 2019-02-01 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10166182

## Citation

> US National Institutes of Health, RePORTER application 10166182, Joint inferences of natural selection between sites and populations (3R01GM127348-02S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10166182. Licensed CC0.

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