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Vizgen is developing the next generation of genomics tools to expand on the capabilities of spatially resolved transcriptomics. Our technology will aide the acceleration of biological research and discovery to advance human health. Access supporting resources by selecting the category below.

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A spatially-resolved transcriptional atlas of the murine dorsal pons at single-cell resolution

ABSTRACT The “dorsal pons”, or “dorsal pontine tegmentum” (dPnTg), is part of the brainstem. It is a complex, densely packed region whose nuclei are involved in the regulation of many vital functions. Notable among them…

Developmental Mouse Brain Common Coordinate Framework

Abstract 3D standard reference brains serve as key resources to understand the spatial organization of the brain and promote interoperability across different studies. However, unlike the adult mouse brain, the lack of standard 3D reference…

Dual lineage origins of neocortical astrocytes

Abstract Astrocytes represent one of the most abundant cell types in the central nervous system, and play an essential role in nearly all aspects of brain functions1. Recent studies have challenged the notion that cortical…

Accurate single-molecule spot detection for image-based spatial transcriptomics with weakly supervised deep learning

Abstract Image-based spatial transcriptomics methods enable transcriptome-scale gene expression measurements with spatial information but require complex, manually-tuned analysis pipelines. We present Polaris, an analysis pipeline for image-based spatial transcriptomics that combines deep learning models for…

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CellsFromSpace: A versatile tool for spatial transcriptomic data analysis with reference-free deconvolution and guided cell type/activity annotation

Abstract Spatial transcriptomics involves capturing the transcriptomic profiles of millions of cells within their spatial contexts, enabling the analysis of cell crosstalk in healthy and diseased organs. However, spatial transcriptomics also raises new computational challenges…

TISSUE: uncertainty-calibrated prediction of single-cell spatial transcriptomics improves downstream analyses

Abstract Whole-transcriptome spatial profiling of genes at single-cell resolution remains a challenge. To address this limitation, spatial gene expression prediction methods have been developed to infer the spatial expression of unmeasured transcripts, but the quality…

Gene count normalization in single-cell imaging-based spatially resolved transcriptomics

Abstract Recent advances in imaging-based spatially resolved transcriptomics (im-SRT) technologies now enable high-throughput profiling of targeted genes and their locations in fixed tissues. Normalization of gene expression data is often needed to account for technical…

SIMVI reveals intrinsic and spatial-induced states in spatial omics data

Abstract Spatial omics analyze gene expression and interaction dynamics in relation to tissue structure and function. However, existing methods cannot model the intrinsic and spatial-induced variation in spatial omics data, thus failing to identify true…

Altered Fhod3 Expression Involved in Progressive High-Frequency Hearing Loss via Dysregulation of Actin Polymerization Stoichiometry in The Cuticular Plate

Abstract Age-related hearing loss (ARHL) is a common sensory impairment with complex underlying mechanisms. In our previous study, we performed a meta-analysis of genome-wide association studies (GWAS) in mice and identified a novel locus on…

Spatiotemporal molecular dynamics of the developing human thalamus

Abstract The thalamus plays a central coordinating role in the brain. Thalamic neurons are organized into spatially-distinct nuclei, but the molecular architecture of thalamic development is poorly understood, especially in humans. To begin to delineate…

Mapping Human Tissues with Highly Multiplexed RNA in situ Hybridization

Abstract In situ transcriptomic techniques promise a holistic view of tissue organization and cell-cell interactions. Recently there has been a surge of multiplexed RNA in situ techniques but their application to human tissues and clinical…

Optimal transport for mapping senescent cells in spatial transcriptomics

Abstract Spatial transcriptomics (ST) provides a unique opportunity to study cellular organization and cell-cell interactions at the molecular level. However, due to the low resolution of the sequencing data additional information is required to utilize…

The quest to map the mouse brain

By combining single-cell sequencing with methods to map the spatial location of gene expression, scientists are unravelling the extraordinary cellular diversity of the brain.

Subcytoplasmic location of translation controls protein output

Summary The cytoplasm is highly compartmentalized, but the extent and consequences of subcytopIasmic mRNA localization in non-polarized cells are largely unknown. We determined mRNA enrichment in TIS granules (TGs) and the rough endopIasmic reticuIum (ER)…

Search and Match across Spatial Omics Samples at Single-cell Resolution

Abstract Spatial omics technologies characterize tissue molecular properties with spatial information, but integrating and comparing spatial data across different technologies and modalities is challenging. A comparative analysis tool that can search, match, and visualize both…

A lack of distinct cell identities in single-cell measurements: revisiting Waddington’s landscape

Abstract The prevailing interpretation of Waddington’s landscape is that attractors in gene expression space produce and stabilize distinct cell types. This notion is often applied in single-cell omics data, where groups of cells are clustered…

HEARTSVG: a fast and accurate method for spatially variable gene identification in large-scale spatial transcriptomic data

Abstract Identifying spatially variable genes (SVGs) is crucial for understanding the spatiotemporal characteristics of diseases and tissue structures, posing a distinctive challenge in spatial transcriptomics research. We propose HEARTSVG, a distribution-free, test-based method for fast…

SpaRx: Elucidate single-cell spatial heterogeneity of drug responses for personalized treatment

ABSTRACT Spatial cellular heterogeneity contributes to differential drug responses in a tumor lesion and potential therapeutic resistance. Recent emerging spatial technologies such as CosMx SMI, MERSCOPE, and Xenium delineate the spatial gene expression patterns at…

Reliable imputation of spatial transcriptome with uncertainty estimation and spatial regularization

Abstract Imputation of missing features in spatial transcriptomics is urgently demanded due to technology limitations, while most existing computational methods suffer from moderate accuracy and cannot estimate the reliability of the imputation. To fill the…

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