Joint inferences of natural selection between sites and populations

NIH RePORTER · NIH · R01 · $199,665 · view on reporter.nih.gov ↗

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
UNIVERSITY OF ARIZONA
Principal Investigator
Ryan Gutenkunst
Activity code
R01
Funding institute
NIH
Fiscal year
2020
Award amount
$199,665
Award type
3
Project period
2019-02-01 → 2024-01-31