Background and objectives: Spatially resolved techniques for exploring the molecular landscape of tissue samples, such as spatial transcriptomics, often result in millions of data points and images too large to view on a regular desktop computer, limiting the possibilities in visual interactive data exploration. TissUUmaps is a free, open-source browser-based tool for GPU-accelerated visualization and interactive exploration of 107+ data points overlaying tissue samples. Methods: Herein we describe how TissUUmaps 3 provides instant multiresolution image viewing and can be customized, shared, and also integrated into Jupyter Notebooks. We introduce new modules where users can visualize markers and regions, explore spatial statistics, perform...
Summary: SpatialExperiment is a new data infrastructure for storing and accessing spatially resolved...
Digital spatial profiling (DSP) is an emerging powerful technology for proteomics and transcriptomic...
Summary: The emergence of megascale single-cell multiplex tissue imaging (MTI) datasets necessitates...
Background and objectives: Spatially resolved techniques for exploring the molecular landscape of ti...
Motivation: Visual assessment of scanned tissue samples and associated molecular markers, such as ge...
Background: Interest in studying the spatial distribution of gene expression in tissues is rapidly i...
Recent advances in spatially resolved transcriptomics have greatly expandedthe knowledge of complex ...
AbstractThe spatial organization of cells and molecules plays a key role in tissue function in homeo...
Recent decades have witnessed the dawn of an era of molecular biology as a data science. Technologic...
Spatial omics data are advancing the study of tissue organization and cellular communication at an u...
Spatial transcriptomics, which is capable of both measuring all gene activity in a tissue sample and...
Knowledge discovery for understanding mechanisms of disease requires the integration of multiple sou...
Spatial transcriptomics technology is increasingly being applied because it enables the measurement ...
Spatial mapping of heterogeneity in gene expression in cancer tissues can improve our understanding ...
Multiplexed mRNA and protein profiling in the spatial context provides important new information ena...
Summary: SpatialExperiment is a new data infrastructure for storing and accessing spatially resolved...
Digital spatial profiling (DSP) is an emerging powerful technology for proteomics and transcriptomic...
Summary: The emergence of megascale single-cell multiplex tissue imaging (MTI) datasets necessitates...
Background and objectives: Spatially resolved techniques for exploring the molecular landscape of ti...
Motivation: Visual assessment of scanned tissue samples and associated molecular markers, such as ge...
Background: Interest in studying the spatial distribution of gene expression in tissues is rapidly i...
Recent advances in spatially resolved transcriptomics have greatly expandedthe knowledge of complex ...
AbstractThe spatial organization of cells and molecules plays a key role in tissue function in homeo...
Recent decades have witnessed the dawn of an era of molecular biology as a data science. Technologic...
Spatial omics data are advancing the study of tissue organization and cellular communication at an u...
Spatial transcriptomics, which is capable of both measuring all gene activity in a tissue sample and...
Knowledge discovery for understanding mechanisms of disease requires the integration of multiple sou...
Spatial transcriptomics technology is increasingly being applied because it enables the measurement ...
Spatial mapping of heterogeneity in gene expression in cancer tissues can improve our understanding ...
Multiplexed mRNA and protein profiling in the spatial context provides important new information ena...
Summary: SpatialExperiment is a new data infrastructure for storing and accessing spatially resolved...
Digital spatial profiling (DSP) is an emerging powerful technology for proteomics and transcriptomic...
Summary: The emergence of megascale single-cell multiplex tissue imaging (MTI) datasets necessitates...