Count phenotypes with excessive zeros are often observed in the biological world. Researchers have studied many statistical methods for mapping the quantitative trait loci (QTLs) of zero-inflated count phenotypes. However, most of the existing methods consist of finding the approximate positions of the QTLs on the chromosome by genome-wide scanning. Additionally, most of the existing methods use the EM algorithm for parameter estimation. In this paper, we propose a Bayesian interval mapping scheme of QTLs for zero-inflated count data. The method takes advantage of a zero-inflated generalized Poisson (ZIGP) regression model to study the influence of QTLs on the zero-inflated count phenotype. The MCMC algorithm is used to estimate the effects and position parameters of QTLs. We use the Haldane map function to realize the conversion between recombination rate and map distance. Monte Carlo simulations are conducted to test the applicability and advantage of the proposed method. The effects of QTLs on the formation of mouse cholesterol gallstones were demonstrated by analyzing an F 2 mouse data set.

中文翻译：

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基于零膨胀广义泊松回归模型的计数性状基因座的贝叶斯区间映射

在生物世界中经常观察到具有过多零的计数表型。研究人员研究了许多统计方法来绘制零膨胀计数表型的数量性状基因座 (QTL)。然而，大多数现有方法包括通过全基因组扫描找到染色体上 QTL 的大致位置。此外，大多数现有方法使用EM算法进行参数估计。在本文中，我们提出了一种用于零膨胀计数数据的 QTL 的贝叶斯区间映射方案。该方法利用零膨胀广义泊松 (ZIGP) 回归模型来研究 QTL 对零膨胀计数表型的影响。MCMC算法用于估计QTL的效应和位置参数。我们使用Haldane map函数来实现重组率和map距离的转换。进行蒙特卡罗模拟以测试所提出方法的适用性和优势。通过分析 F 2 小鼠数据集证明了 QTL 对小鼠胆固醇胆结石形成的影响。