多亲本杂交低覆盖度测序基因分型数据中缺失标记的高效填充
Efficient imputation of missing markers in low-coverage genotyping-by-sequencing data from multiparental crosses.
作者信息
Huang B Emma, Raghavan Chitra, Mauleon Ramil, Broman Karl W, Leung Hei
机构信息
Computational Informatics and Food Futures Flagship, Commonwealth Scientific and Industrial Research Organization, Dutton Park, Queensland, Australia 4102.
出版信息
Genetics. 2014 May;197(1):401-4. doi: 10.1534/genetics.113.158014. Epub 2014 Feb 28.
Abstract
We consider genomic imputation for low-coverage genotyping-by-sequencing data with high levels of missing data. We compensate for this loss of information by utilizing family relationships in multiparental experimental crosses. This nearly quadruples the number of usable markers when applied to a large rice Multiparent Advanced Generation InterCross (MAGIC) study.
摘要
我们考虑对具有高缺失数据水平的低覆盖度测序基因分型数据进行基因组填充。我们通过利用多亲本实验杂交中的家系关系来弥补这种信息损失。当应用于一项大型水稻多亲本高级世代互交（MAGIC）研究时，这几乎使可用标记的数量增加了四倍。
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