A bivariate zero-inflated negative binomial model and its applications to biomedical settings.
A bivariate zero-inflated negative binomial model and its applications to biomedical settings.
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DOI：
10.1177/09622802231172028
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发表时间：
2023-07
影响因子：
2.3
通讯作者：
Wu, Di
中科院分区：
文献类型：
--
作者：
Cho, Hunyong;Liu, Chuwen;Preisser, John S.;Wu, Di
关键词：
零膨胀负二项分布由于其模拟过零和过分散的能力，已广泛用于各种生物医学环境中的计数数据分析。当存在相关计数变量时，二元模型对于理解它们的完整分布特征至关重要。例如，在稀疏的单细胞RNA测序数据中测量两个基因的相关性，以及在两种不同的牙齿表面类型上建模龋齿计数指数。为此，我们开发了一个富参数化的二元零膨胀负二项式模型，该模型具有简单的潜在变量框架和八个具有直观解释的自由参数。在scRNA-seq数据示例中，相关性是在调整了由多余零表示的退出事件的影响后估计的。在龋齿数据中，我们分析了木糖醇含片治疗对两种龋齿特征的边际均值和其他反应模式的影响。一个R包“bzinb”可以在综合R档案网络上获得。
The zero-inflated negative binomial distribution has been widely used for count data analyses in various biomedical settings due to its capacity of modeling excess zeros and overdispersion. When there are correlated count variables, a bivariate model is essential for understanding their full distributional features. Examples include measuring correlation of two genes in sparse single-cell RNA sequencing data and modeling dental caries count indices on two different tooth surface types. For these purposes, we develop a richly parametrized bivariate zero-inflated negative binomial model that has a simple latent variable framework and eight free parameters with intuitive interpretations. In the scRNA-seq data example, the correlation is estimated after adjusting for the effects of dropout events represented by excess zeros. In the dental caries data, we analyze how the treatment with Xylitol lozenges affects the marginal mean and other patterns of response manifested in the two dental caries traits. An R package “bzinb” is available on Comprehensive R Archive Network.
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