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A computational framework for improving genetic variants identification from 5,061 sheep sequencing data

Shangqian Xie Karissa Isaacs Gabrielle Becker Brenda M.Murdoch

畜牧与生物技术杂志（英文版）2023，Vol.14Issue(6)：2332-2344,13.

畜牧与生物技术杂志（英文版）2023，Vol.14Issue(6)：2332-2344,13.DOI:10.1186/s40104-023-00923-3

A computational framework for improving genetic variants identification from 5,061 sheep sequencing data

Shangqian Xie ¹Karissa Isaacs ²Gabrielle Becker ¹Brenda M.Murdoch¹

作者信息

1. Department of Animal,Veterinary & Food Sciences,University of Idaho,Moscow,ID,USA
2. Superior Farms,California,USA
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摘要

关键词

Computational framework/Genetic variants/Multiple samples/Sheep

Key words

Computational framework/Genetic variants/Multiple samples/Sheep

引用本文复制引用

Shangqian Xie,Karissa Isaacs,Gabrielle Becker,Brenda M.Murdoch..A computational framework for improving genetic variants identification from 5,061 sheep sequencing data[J].畜牧与生物技术杂志（英文版）,2023,14(6):2332-2344,13.

基金项目

We would like to thank Superior Farms sheep producers and IBEST for their support. This material is based upon work that is supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, award numbers USDA-NIFA-IDA1566 and financial support from the Idaho Global Entrepreneurial Mission. （）

畜牧与生物技术杂志（英文版）

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ISSN：1674-9782

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