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.

中文翻译：

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使用全长 scRNA-seq 数据检测异构体的障碍


背景早期的单细胞 RNA-seq (scRNA-seq) 研究表明，即使在匹配的批量 RNA-seq 样本中检测到多种同工型，单个细胞中的基因产生多个同工型也是不寻常的。然而，这些研究通常没有考虑丢失或亚型量化错误的影响，可能会混淆这些分析的结果。结果在本研究中，我们采用基于模拟的方法，其中明确考虑了丢失和异构体量化误差。我们通过模拟来探究使用 scRNA-seq 研究选择性剪接的可能性。此外，我们询问必须克服哪些限制才能使剪接分析可行。我们发现与 scRNA-seq 相关的高丢失率是研究选择性剪接的主要障碍。在小鼠和其他成熟的模型生物中，同种型定量错误率相对较低，对剪接分析造成的障碍较小。我们发现不同的异构体选择模型有意义地改变了我们的模拟结果。结论 为了通过单细胞 RNA-seq 准确研究选择性剪接，需要更好地了解同种型选择以及与 scRNA-seq 相关的错误。 scRNA-seq 捕获效率的提高也将是有益的。在实现上述部分或全部目标之前，我们不建议尝试使用 scRNA-seq 解析单个细胞中的异构体。