Recent advances in single-cell technologies are providing exciting opportunities for dissecting tissue heterogeneity and investigating cell identity, fate and function. This is a pristine, exploding field that is flooding biologists with a new wave of data, each with its own specificities in terms of complexity and information content. The integrative analysis of genomic data, collected at different molecular layers from diverse cell populations, holds promise to address the full-scale complexity of biological systems. However, the combination of different single-cell genomic signals is computationally challenging, as these data are intrinsically heterogeneous for experimental, technical and biological reasons. Here, we describe the computational methods for the integrative analysis of single-cell genomic data, with a focus on the integration of single-cell RNA sequencing datasets and on the joint analysis of multimodal signals from individual cells.

中文翻译：

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单细胞数据综合分析的计算方法。

单细胞技术的最新进展为剖析组织异质性和研究细胞特性、命运和功能提供了令人兴奋的机会。这是一个原始的、爆炸性的领域，正在用新一波数据淹没生物学家，每个数据在复杂性和信息内容方面都有自己的特点。从不同细胞群的不同分子层收集的基因组数据的综合分析有望解决生物系统的全面复杂性。然而，不同单细胞基因组信号的组合在计算上具有挑战性，因为由于实验、技术和生物学原因，这些数据本质上是异质的。在这里，我们描述了单细胞基因组数据综合分析的计算方法，