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Single Cell Atlas: a single-cell multi-omics human cell encyclopedia
Single-cell sequencing datasets are key in biology and medicine for unraveling insights into heterogeneous cell populations with unprecedented...
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The technological landscape and applications of single-cell multi-omics
Single-cell multi-omics technologies and methods characterize cell states and activities by simultaneously integrating various single-modality omics...
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A fast, scalable and versatile tool for analysis of single-cell omics data
Single-cell omics technologies have revolutionized the study of gene regulation in complex tissues. A major computational challenge in analyzing...
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Progress in single-cell multimodal sequencing and multi-omics data integration
With the rapid advance of single-cell sequencing technology, cell heterogeneity in various biological processes was dissected at different omics...
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Application of single-cell multi-omics approaches in horticulture research
Cell heterogeneity shapes the morphology and function of various tissues and organs in multicellular organisms. Elucidation of the differences among...
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scDesign3 generates realistic in silico data for multimodal single-cell and spatial omics
We present a statistical simulator, scDesign3, to generate realistic single-cell and spatial omics data, including various cell states, experimental...
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Single-cell omics traces the heterogeneity of prostate cancer cells and the tumor microenvironment
Prostate cancer is one of the more heterogeneous tumour types. In recent years, with the rapid development of single-cell sequencing and spatial...
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Multimodal Methods for Knowledge Discovery from Bulk and Single-Cell Multi-Omics Data
Multi-omics measurements (bulk and single-cell) are essential to depict the cellular states comprehensively and thus could derive a deep...
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Gene Regulatory Network Modeling Using Single-Cell Multi-Omics in Plants
Single-cell multi-omics technology can be applied to plant cells to characterize gene expression and open chromatin regions in individual cells. In...
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A machine learning one-class logistic regression model to predict stemness for single cell transcriptomics and spatial omics
Cell annotation is a crucial methodological component to interpreting single cell and spatial omics data. These approaches were developed for single...
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Spatial omics technologies at multimodal and single cell/subcellular level
Spatial omics technologies enable a deeper understanding of cellular organizations and interactions within a tissue of interest. These assays can...
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Current and future perspectives of single-cell multi-omics technologies in cardiovascular research
Single-cell technology has become an indispensable tool in cardiovascular research since its first introduction in 2009. Here, we highlight the...
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Single-cell multi-omics profiling of human preimplantation embryos identifies cytoskeletal defects during embryonic arrest
Human in vitro fertilized embryos exhibit low developmental capabilities, and the mechanisms that underlie embryonic arrest remain unclear. Here...
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Single-cell multi-omics integration for unpaired data by a siamese network with graph-based contrastive loss
BackgroundSingle-cell omics technology is rapidly develo** to measure the epigenome, genome, and transcriptome across a range of cell types....
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Multi-omics single-cell data integration and regulatory inference with graph-linked embedding
Despite the emergence of experimental methods for simultaneous measurement of multiple omics modalities in single cells, most single-cell datasets...
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Single-cell multi-omics sequencing of human spermatogenesis reveals a DNA demethylation event associated with male meiotic recombination
Human spermatogenesis is a highly ordered process; however, the roles of DNA methylation and chromatin accessibility in this process remain largely...
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Single-cell spatial multi-omics and deep learning dissect enhancer-driven gene regulatory networks in liver zonation
In the mammalian liver, hepatocytes exhibit diverse metabolic and functional profiles based on their location within the liver lobule. However, it is...
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TACCO unifies annotation transfer and decomposition of cell identities for single-cell and spatial omics
Transferring annotations of single-cell-, spatial- and multi-omics data is often challenging owing both to technical limitations, such as low spatial...
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Single-cell multi-omics analysis of lineage development and spatial organization in the human fetal cerebellum
Human cerebellum encompasses numerous neurons, exhibiting a distinct developmental paradigm from cerebrum. Here we conducted scRNA-seq, scATAC-seq...
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Deep Learning Methods for Single-Cell Omics Data
Deep learning has become an appealing computational tool for analyzing single-cell omics data. We review statistical and modeling insights that have...