Lulu Shang


Room 206, No. 6 Science Building


Spatial transcriptomics are a collection of genomic technologies that have enabled transcriptomic profiling on tissues with spatial localization information. Analyzing spatial transcriptomic data is computationally challenging, as the data collected from various spatial transcriptomic technologies are often noisy and display substantial spatial correlation across tissue locations. Here, we develop a spatially aware dimension reduction method, SpatialPCA, that can extract a low dimensional representation of the spatial transcriptomics data with biological signal and preserved spatial correlation structure. We illustrate the benefits of SpatialPCA for spatial domain detection and explore its utility for trajectory inference on the tissue and for high-resolution spatial map construction.

Short bio

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 in 2023. Previously, she obtained bachelor’s degree in Biology from the Zhiyuan College at Shanghai Jiao Tong University. She is generally interested in developing effective and efficient statistical and computational methods for analyzing large-scale genetic and genomic datasets.