Pumping the brakes on RNA velocity by understanding and interpreting RNA velocity estimates.
Pumping the brakes on RNA velocity by understanding and interpreting RNA velocity estimates.
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DOI：
10.1186/s13059-023-03065-x
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发表时间：
2023-10-26
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影响因子：
12.3
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单细胞 RNA 速度分析提供了预测基因表达时间动态的潜力。在许多系统中，RNA 速度已被观察到产生一个矢量场，该矢量场定性地反映了系统的已知特征。然而，RNA 速度估计的局限性仍然没有得到很好的理解。我们分析了 RNA 速度工作流程中不同步骤对方向和速度的影响。我们考虑映射到嵌入的高维速度估计和低维速度向量场。我们得出的结论是，将速度估计映射到嵌入上的转移概率方法可以有效地在嵌入空间中进行插值。我们的研究结果揭示了 RNA 速度工作流程对通过观测数据的 k 最近邻 (k-NN) 图进行平滑的显着依赖。当 k-NN 图无法准确表示真实数据结构时，这种依赖会导致高维和低维设置中方向和速度的估计误差相当大；这是真实数据的一个未知特征。除了非常低的噪声设置外，RNA 速度在低维和高维空间中的速度估计方面都表现不佳。我们引入了一种新颖的质量测量方法，可以识别何时不应使用 RNA 速度。我们的研究结果强调了 RNA 速度工作流程中选择的重要性，并强调了数据分析的关键局限性。我们建议不要过度解释使用 RNA 速度的表达动态，特别是在速度方面。最后，我们强调使用 RNA 速度来评估低维嵌入的正确性是循环的。在线版本包含可在 10.1186/s13059-023-03065-x 获取的补充材料。
RNA velocity analysis of single cells offers the potential to predict temporal dynamics from gene expression. In many systems, RNA velocity has been observed to produce a vector field that qualitatively reflects known features of the system. However, the limitations of RNA velocity estimates are still not well understood. We analyze the impact of different steps in the RNA velocity workflow on direction and speed. We consider both high-dimensional velocity estimates and low-dimensional velocity vector fields mapped onto an embedding. We conclude the transition probability method for mapping velocity estimates onto an embedding is effectively interpolating in the embedding space. Our findings reveal a significant dependence of the RNA velocity workflow on smoothing via the k-nearest-neighbors (k-NN) graph of the observed data. This reliance results in considerable estimation errors for both direction and speed in both high- and low-dimensional settings when the k-NN graph fails to accurately represent the true data structure; this is an unknown feature of real data. RNA velocity performs poorly at estimating speed in both low- and high-dimensional spaces, except in very low noise settings. We introduce a novel quality measure that can identify when RNA velocity should not be used. Our findings emphasize the importance of choices in the RNA velocity workflow and highlight critical limitations of data analysis. We advise against over-interpreting expression dynamics using RNA velocity, particularly in terms of speed. Finally, we emphasize that the use of RNA velocity in assessing the correctness of a low-dimensional embedding is circular. The online version contains supplementary material available at 10.1186/s13059-023-03065-x.