Benchmarking RNA velocity methods across 17 independent studies

对 17 项独立研究中的 RNA 速度方法进行基准测试

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Abstract

RNA velocity techniques offer great potential for unveiling trajectories of cell state transitions in different biological contexts. While diverse computational methods have been developed, there are no evidence-based guidelines for best-practice in RNA velocity inference. Here, we conduct a benchmark study of 15 existing RNA velocity methods across 17 independent datasets, incorporating multiple validation strategies. We evaluate performance across three key dimensions: accuracy, stability, and usability. Our data showed no single method exhibited superior performance in all the assessments, and unexpected underperformance was observed in certain cases. Based on these findings, we establish scenario-based suggestions of best-practice to assist users in selecting the method best suited to their data and analytical needs.

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