VistoSeg: processing utilities for high-resolution Visium/Visium-IF images for spatial transcriptomics data thumbnail
VistoSeg: processing utilities for high-resolution Visium/Visium-IF images for spatial transcriptomics data
www.biorxiv.org
from VistoSeg is in CSV file format that can be easily incorporated into R objects like SpatialExperiment (29), Seurat (30), or Python objects like AnnData (31), which are two commonly used languages for analysis of spatial transcriptomic data. Several software packages have been developed in the Py
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  • from VistoSeg is in CSV file format that can be easily incorporated into R objects like SpatialExperiment (29), Seurat (30), or Python objects like AnnData (31), which are two commonly used languages for analysis of spatial transcriptomic data.
  • Several software packages have been developed in the Python and R programming languages for cell segmentation and subsequent registration of microscopy images to anatomical reference atlases (14,15)
  • Moreover, commercial image analysis software for Visium (2) or pathology imaging software (3) do not support quantitative analysis of Visium images for integration with molecular gene expression data
  • nuclei segmentation of H&E images can be used to estimate the number of nuclei in each Visium spot or to identify cell types based on classic morphologies (4,5).

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