Revealing the vectors of cellular identity with single-cell genomics.
Revealing the vectors of cellular identity with single-cell genomics.
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DOI：
10.1038/nbt.3711
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发表时间：
2016-11-08
影响因子：
46.9
通讯作者：
Yosef N
中科院分区：
文献类型：
--
作者：
Wagner A;Regev A;Yosef N
单细胞基因组学现在已经有可能创建一个全面的人类细胞图谱。与此同时，它重新定义了细胞的身份和类型，以及它们受细胞分子回路调节的方式。新兴的计算分析方法，特别是在单细胞RNA测序（scRNA-seq）中，已经开始以数据驱动的方式揭示细胞身份的不同同时方面，从离散细胞类型的分类到连续的动态转变和空间位置。这些发展最终将允许细胞被表示为“基本矢量”的叠加，每个基本矢量决定细胞组织和功能的不同（但可能依赖）方面。然而，计算方法也必须克服相当大的挑战，从处理技术噪音和数据规模，以形成新的生物学抽象。随着单细胞实验规模的不断增加，新的计算方法对于构建和表征细胞身份的参考图谱至关重要。
Single-cell genomics has now made it possible to create a comprehensive atlas of human cells. At the same time, it has reopened definitions of a cell’s identity and type and of the ways in which they are regulated by the cell’s molecular circuitry. Emerging computational analysis methods, especially in single-cell RNA sequencing (scRNA-seq), have already begun to reveal, in a data-driven way, the diverse simultaneous facets of a cell’s identity, from a taxonomy of discrete cell types to continuous dynamic transitions and spatial locations. These developments will eventually allow a cell to be represented as a superposition of ‘basis vectors’, each determining a different (but possibly dependent) aspect of cellular organization and function. However, computational methods must also overcome considerable challenges—from handling technical noise and data scale to forming new abstractions of biology. As the scale of single-cell experiments continues to increase, new computational approaches will be essential for constructing and characterizing a reference map of cell identities.