Statistical Bioinformatics Seminar: Dr Lulu Shang (MD Anderson Cancer Center)

Hosted by Sydney Precision Data Science Centre 

Speaker: Dr Lulu Shang (MD Anderson Cancer Center) 

Abstract: Spatial transcriptomics is a collection of genomic technologies that enable
transcriptomic profiling of tissues with spatial localization information.  An essential
task in spatial transcriptomics involves identifying genes with spatial expression
patterns, known as spatially variable genes (SVGs).  Importantly, a subset of SVGs
displays diverse spatial expression patterns within a given cell type, thus representing
key transcriptomic signatures underlying cellular heterogeneity.  Here, we present
Celina, a statistical method for systematically detecting this subset of cell
type-specific SVGs (ct-SVGs).  Celina utilizes a spatially varying coefficient model to
accurately capture each gene’s spatial expression pattern in relation to the
distribution of cell types across tissue locations, ensuring effective type I error
control and high statistical power.  We evaluated the performance of Celina through
comprehensive simulations and applications to five real datasets, where we also adapted
and examined existing methods originated from other analytic settings to detect
ct-SVGs.  Celina proves powerful compared to these ad hoc method adaptations in single
cell resolution spatial transcriptomics and stands as the only effective solution for
spot resolution spatial transcriptomics.  The ct-SVGs detected by Celina also enable
novel biologically informed downstream analyses, unveiling functional cellular
heterogeneity at an unprecedented scale.  

About the speaker: Dr Shang is a tenure-track Assistant Professor in the Department of
Biostatistics at MD Anderson Cancer Center.  She obtained her PhD degree from the
Department of Biostatistics at the University of Michigan.  She is primarily interested
in developing effective and efficient statistical and computational methods for
analyzing large-scale genetic and genomic datasets.  Specifically, her focus is on
integrating multi-omics data in single-cell and spatial transcriptomics, ultimately
connecting molecular insights with clinical applications.  

This event will be online.  

Zoom: https://uni-sydney.zoom.us/j/84087321707