Published January 21, 2021 | Version 1.0.0
Dataset Open

Data From: Powerful detection of polygenic selection and environmental adaptation in US beef cattle

  • 1. University of Missouri
  • 2. Texas A&M University

Description

GEMMA output containing summary statistics for generation proxy selection mapping (GPSM) and environmental GWAS (envGWAS) selection analyses from 
Rowan et al. "Powerful detection of polygenic selection and environmental adaptation in US beef cattle" 2021
https://doi.org/10.1101/2020.03.11.988121    

File names identify the analysis run, for example
"Gelbvieh_envgwas_desert_summary_stats.txt.gz"
Is the Gelbvieh dataset analyzed using the Desert ecoregion as the dependent variable 
in a univariate envGWAS model. 

Files are formated according to GEMMA output.

Notes

This project was supported by Agriculture and Food Research Initiative Competitive Grant no. 2016-68004-24827 from the USDA National Institute of Food and Agriculture awarded to JED. https://reeis.usda.gov/web/crisprojectpages/1008909-identifyinglocal-adaptation-and-creating-region-specific-genomic-predictions-in-beef-cattle.html Funders did not play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The raw data underlying the results presented in the study are available from the Red Angus Association of America (https://redangus.org/contact-us/, Ryan Boldt, Director of Breed Improvement, ryan@redangus.org, (940) 387-3502 ext. 12), American Simmental Association (https://simmental.org/site/index.php/contact#asadirectors, Jackie Atkins, Director Science and Education Operations, jatkins@simmgene.com, (406)587-4531), and American Gelbvieh Association (https://gelbvieh.org/about/contact, Megan Slater, Executive Director, megans@gelbvieh.org, (303)465-2333, Ext 485) under a Data Use Agreement, but are not publicly available. Derived data (analytical results) are however available as supplementary files associated with this publication.

Files

RowanEtAl2021SummaryStats.zip

Files (1.5 GB)

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Additional details

Related works

Is cited by
Preprint: 10.1101/2020.03.11.988121 (DOI)