Methods and applications for single-cell and spatial multi-omics

By K. Vandereyken, A. Sifrim, B. Thienpont, T. Voet. Nature reviews genetics, 2023

980 citations recorded by the source corpus.

The joint analysis of the genome, epigenome, transcriptome, proteome and/or metabolome from single cells is transforming our understanding of cell biology in health and disease. In less than a decade, the field has seen tremendous technological revolutions that enable crucial new insights into the interplay between intracellular and intercellular molecular mechanisms that govern development, physiology and pathogenesis. In this Review, we highlight advances in the fast-developing field of single-cell and spatial multi-omics technologies (also known as multimodal omics approaches), and the computational strategies needed to integrate information across these molecular layers. We demonstrate their impact on fundamental cell biology and translational research, discuss current challenges and provide an outlook to the future. In this Review, the authors discuss the latest advances in profiling multiple molecular modalities from single cells, including genomic, transcriptomic, epigenomic and proteomic information. They describe the diverse strategies for separately analysing different modalities, how the data can be computationally integrated, and approaches for obtaining spatially resolved data.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/223611cdb8c0b4d8ffcd92e221af105082e4ffb3

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In Molecular Biology

1. Li Zhan
2. Tianzhi Wu
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4. Wenli Tang
5. Zijing Xie
6. Shuangbin Xu
7. Xiao Luo
8. Qianwen Wang

Citations in the corpus

• Using clusterProfiler to characterize multiomics data (2024, positive): “Single-cell sequencing methodologies have empowered researchers with the capability to scrutinize gene expression profiles at an individual cell granularity, thereby probing the intrinsic cellular heterogeneity with remarkable precision 46 .”
• Gene regulatory network inference in the era of single-cell multi-omics (2023, background): “For paired multi-omics technologies, a systematic benchmark comparing their varying coverage and sensitivity to their single-omic counterparts is missing 150 .”