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Obstacles to detecting isoforms using full-length scRNA-seq data

机译:使用全长SCRNA-SEQ数据检测同种型的障碍

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Background Early single-cell RNA-seq (scRNA-seq) studies suggested that it was unusual to see more than one isoform being produced from a gene in a single cell, even when multiple isoforms were detected in matched bulk RNA-seq samples. However, these studies generally did not consider the impact of dropouts or isoform quantification errors, potentially confounding the results of these analyses. Results In this study, we take a simulation based approach in which we explicitly account for dropouts and isoform quantification errors. We use our simulations to ask to what extent it is possible to study alternative splicing using scRNA-seq. Additionally, we ask what limitations must be overcome to make splicing analysis feasible. We find that the high rate of dropouts associated with scRNA-seq is a major obstacle to studying alternative splicing. In mice and other well-established model organisms, the relatively low rate of isoform quantification errors poses a lesser obstacle to splicing analysis. We find that different models of isoform choice meaningfully change our simulation results. Conclusions To accurately study alternative splicing with single-cell RNA-seq, a better understanding of isoform choice and the errors associated with scRNA-seq is required. An increase in the capture efficiency of scRNA-seq would also be beneficial. Until some or all of the above are achieved, we do not recommend attempting to resolve isoforms in individual cells using scRNA-seq.
机译:背景技术早期单细胞RNA-SEQ(ScRNA-SEQ)研究表明,即使在匹配的大量的批量RNA-SEQ样品中检测到多种同种型,也是不寻常的。然而,这些研究通常不考虑辍学或同种型量化误差的影响,可能会混淆这些分析的结果。结果在这项研究中,我们采用了一种基于模拟的方法,其中我们明确地解释了辍学和异构量化误差。我们使用我们的模拟来询问使用ScrNA-SEQ的替代剪接有多大程度。此外,我们询问必须克服哪些限制以使拼接分析可行。我们发现与ScrNA-SEQ相关的辍学率高是研究替代拼接的主要障碍。在小鼠和其他良好的模型生物中,相对低的同种型量化误差率为剪接分析呈较小的障碍。我们发现不同型号的同种型选择有意义地改变我们的模拟结果。结论,准确研究单细胞RNA-SEQ的替代剪接,更好地了解同种类选择以及与ScrNA-SEQ相关的误差是必需的。 ScrNA-SEQ捕获效率的增加也是有益的。直到上述部分或全部实现,我们不建议尝试使用SCRNA-SEQ在单个细胞中解析同种型。

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