Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression.
Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression.
复制标题
表征单细胞RNA-seq中的噪声结构可将真实性与技术随机等位基因表达区分开。
DOI：
10.1038/ncomms9687
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发表时间：
2015-10-22
影响因子：
16.6
通讯作者：
Marioni JC
中科院分区：
文献类型：
--
作者：
Kim JK;Kolodziejczyk AA;Ilicic T;Teichmann SA;Marioni JC
单细胞RNA测序（scRNA-seq）有助于鉴定新的细胞类型和基因调控网络，以及分析基因表达的动力学和等位基因特异性表达模式。然而，为了促进这种分析，将生物变异性与影响scRNA-seq协议的高水平技术噪音分开至关重要。在这里，我们描述并验证了一个生成统计模型，该模型可以在外部RNA spike-in的帮助下准确量化技术噪声。将我们的方法应用于研究单个细胞中的随机等位基因特异性表达，我们证明了很大一部分随机等位基因特异性表达可以通过技术噪声来解释，特别是对于低表达和中等表达的基因：我们预测只有17.8%的随机等位基因特异性表达模式可归因于生物噪声，其余的归因于技术噪声。
Single-cell RNA-sequencing (scRNA-seq) facilitates identification of new cell types and gene regulatory networks as well as dissection of the kinetics of gene expression and patterns of allele-specific expression. However, to facilitate such analyses, separating biological variability from the high level of technical noise that affects scRNA-seq protocols is vital. Here we describe and validate a generative statistical model that accurately quantifies technical noise with the help of external RNA spike-ins. Applying our approach to investigate stochastic allele-specific expression in individual cells we demonstrate that a large fraction of stochastic allele-specific expression can be explained by technical noise, especially for low and moderately expressed genes: we predict that only 17.8% of stochastic allele-specific expression patterns are attributable to biological noise with the remainder due to technical noise.