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29 kwi 2020 · Overall, we have shown the capabilities of SpaOTsc to (1) map between scRNA-seq data and spatial data, (2) infer spatial distances between single cells, (3) quantitatively compare spatial...
- Tissue-specific enhancer–gene maps from multimodal single-cell data ...
Abstract. Translating genome-wide association study (GWAS)...
- Gene trajectory inference for single-cell data by optimal transport ...
To visualize the geometry of all genes, we convert pairwise...
- Tissue-specific enhancer–gene maps from multimodal single-cell data ...
19 gru 2023 · Until now, only a few methods allow the analysis of single-cell genomics datasets at a sample level. PhEMD (Chen et al, 2020) is based on earth moving distance (EMD) to measure the distance between specimens (single-cell samples), where the distance between specimens was based on clustering representations from a diffusion-based space. This ...
Here, we developed a method for visualizing high-dimensional single-cell gene expression datasets, similarity weighted nonnegative embedding (SWNE), which captures both local and global structure in the data, while enabling the genes and biological factors that separate the cell types and trajectories to be embedded directly onto the visualization.
26 kwi 2018 · High-throughput mapping of cellular differentiation hierarchies from single-cell data promises to empower systematic interrogations of vertebrate development and disease. Here we applied single-cell RNA sequencing to >92,000 cells from zebrafish embryos during the first day of development.
High-throughput mapping of cellular differentia tion hierarchies from single-cell data promises to empowersystematic interrogations of vertebrate development and disease. Here we applied single-cell RNA sequencing to >92,000 cells from zebrafish embryos during the first day of development.
