Inferring the developmental potential of single cells from scRNA-Seq data and reconstructing the pseudo-temporal path of cell development are fundamental but challenging tasks in single-cell analysis. Although single-cell transcriptional diversity (SCTD) measured by the number of expressed genes per cell has been widely used as a hallmark of developmental potential, it may lead to incorrect estimation of differentiation states in some cases where gene expression does not decrease monotonously during the development process. In this study, we propose a novel metric called single-cell transcriptional complexity (SCTC), which draws on insights from the economic complexity theory and takes into account the sophisticated structure information of scRNA-Seq count matrix. We show that SCTC characterizes developmental potential more accurately than SCTD, especially in the early stages of development where cells typically have lower diversity but higher complexity than those in the later stages. Based on the SCTC, we provide an unsupervised method for accurate, robust, and transferable inference of single-cell pseudotime. Our findings suggest that the complexity emerging from the interplay between cells and genes determines the developmental potential, providing new insights into the understanding of biological development from the perspective of complexity theory.

中文翻译：

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SCTC：从单细胞转录复杂性推断发育潜力

从 scRNA-Seq 数据推断单细胞的发育潜力并重建细胞发育的伪时间路径是单细胞分析中的基本但具有挑战性的任务。尽管通过每个细胞表达基因的数量来衡量的单细胞转录多样性（SCTD）已被广泛用作发育潜力的标志，但在某些情况下，当基因表达在发育过程中不单调减少时，它可能会导致对分化状态的错误估计。发展过程。在这项研究中，我们提出了一种称为单细胞转录复杂性（SCTC）的新指标，它借鉴了经济复杂性理论的见解，并考虑了 scRNA-Seq 计数矩阵的复杂结构信息。我们表明，SCTC 比 SCTD 更准确地表征发育潜力，特别是在发育早期阶段，细胞通常比后期阶段具有较低的多样性，但复杂性较高。基于 SCTC，我们提供了一种无监督方法，用于准确、鲁棒且可转移的单细胞伪时间推断。我们的研究结果表明，细胞和基因之间相互作用产生的复杂性决定了发育潜力，为从复杂性理论的角度理解生物发育提供了新的见解。