polyRAD: Genotype Calling with Uncertainty from Sequencing Data in Polyploids and Diploids
polyRAD: Genotype Calling with Uncertainty from Sequencing Data in Polyploids and Diploids
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DOI：
10.1534/g3.118.200913
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发表时间：
2019-03-01
影响因子：
2.6
通讯作者：
Sacks, Erik J.
中科院分区：
文献类型：
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作者：
Clark, Lindsay V.;Lipka, Alexander E.;Sacks, Erik J.
低或不均匀的读数深度是GBS和RAD-SEQ的常见缺陷，导致高缺失率，杂合子被误认为纯合子，杂合子多倍体中的等位基因拷贝数不确定。贝叶斯基因型呼叫可以缓解这些问题，但以前只在需要参考基因组或使用可能不适合人群的先验的软件中实现。在这里，我们提出了几种新的贝叶斯算法来估计基因型后验概率，所有这些算法都在一个新的R包PolyRAD中实现。可以指定适当的先验来定位群体、处于Hardy-Weinberg平衡的群体或结构化群体，并且在每种情况下都可以通过连锁标记的基因类型来获得信息。PolyRAD软件从几个现有的管道中导入读取深度，并输出适合于全基因组关联和基因组预测等分析的连续或离散的数字基因型。
Low or uneven read depth is a common limitation of genotyping-by-sequencing (GBS) and restriction site-associated DNA sequencing (RAD-seq), resulting in high missing data rates, heterozygotes miscalled as homozygotes, and uncertainty of allele copy number in heterozygous polyploids. Bayesian genotype calling can mitigate these issues, but previously has only been implemented in software that requires a reference genome or uses priors that may be inappropriate for the population. Here we present several novel Bayesian algorithms that estimate genotype posterior probabilities, all of which are implemented in a new R package, polyRAD. Appropriate priors can be specified for mapping populations, populations in Hardy-Weinberg equilibrium, or structured populations, and in each case can be informed by genotypes at linked markers. The polyRAD software imports read depth from several existing pipelines, and outputs continuous or discrete numerical genotypes suitable for analyses such as genome-wide association and genomic prediction.