Identifying cell-type-specific spatially variable genes for Visium HD data

Haotian Zhuang Speaker
Duke University
 
Xinyi Shang Co-Author
University of Massachusetts Amherst
 
Wenpin Hou Co-Author
Columbia University
 
Zhicheng Ji Co-Author
Duke University
 
Sunday, Aug 2: 3:05 PM - 3:20 PM
3598 
Contributed Papers 
Thomas M. Menino Convention & Exhibition Center 
Spatially variable genes (SVGs) reveal the molecular and functional heterogeneity of cells across different spatial regions of a tissue. We found that sample-wide SVGs, identified by previous methods across the whole sample, largely overlap with cell-type marker genes derived from single-cell gene expression, leaving the spatial location information largely underutilized. We developed ctSVG, a computational method specifically tailored for Visium HD spatial transcriptomics at single-cell resolution. ctSVG accurately assigns Visium squares to cells and identifies cell-type-specific SVGs. We show that cell-type-specific SVGs identified by ctSVG include many new genes that do not overlap with sample-wide SVGs or cell-type marker genes, and that these genes reveal important biological functions in real spatial datasets.

Keywords

Spatial transcriptomics

Visium HD

Spatially variable gene (SVG) 

Main Sponsor

Section on Statistics in Genomics and Genetics