Multi-omics at single-cell resolution: comparison of experimental and data fusion approaches.

Biological samples are inherently heterogeneous and complex. Tackling this complexity requires innovative technological and analytical solutions. Recent advances in high-throughput single-cell isolation and nucleic acid barcoding methods are rapidly changing the technological landscape of biological sciences and now make it possible to measure the (epi)genomic, transcriptomic, or proteomic state of individual cells. In addition, few experimental approaches enable multi-omics measurements of the same cell. However, merging-omics data collected from different experiments remains a considerable challenge. Although several strategies for merging transcriptomics datasets have recently been introduced, cell-to-cell variability and heterogeneity remains one of the confounding factors limiting data fusion and integration. Here, we focus our discussion on the latest single-cell technological and analytical solutions to achieve high data dimensionality and resolution. Obtaining datasets with a wealth of multi-omics information will undoubtedly provide new avenues for researchers to unravel the complexity of biological samples encountered in modern biological research and molecular diagnostics.