Spatial omics profiling technologies
Emerging spatial omics methods enable the charting of cellular heterogeneity, complex tissue architectures and dynamic changes during development and disease
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Revealing gene function with statistical inference at single-cell resolution
Single-cell, spatial and multi-omic profiling technologies generate large-scale data that reveal the output of genome-scale experiments across diverse cells, tissues and organisms. Cole Trapnell reviews the underlying core statistical challenges that need to be tackled to harness the power of these technologies and advance our understanding of gene function in health and disease.
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Single-cell omics
Many biological phenomena are either invisible or only partially characterized when interrogated using standard analyses that average data across a bulk population of cells. Now, technological advances are providing unprecedented opportunities to analyse the complexities of biological systems at the single-cell level. High-throughput analyses of the genomes, transcriptomes and proteomes of single cells are yielding novel and important insights into diverse processes such as development, gene-expression dynamics, tissue heterogeneity and disease pathogenesis. In this Focus issue, we highlight the transformative potential of single-cell omics approaches.
