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Statistical methods for single-cell and spatial RNA-seq
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Dr. Christina Kendziorski’s research concerns statistical methods and software for computational biology and genomics. Her group develops statistical methods and software for the analysis of data from high-throughput genomics experiments and have considerable expertise in the experimental design and analysis of bulk RNA-seq studies and in single-cell RNA-seq. The group also uses high-throughput data from multiple studies to address critical challenges in the treatment of ovarian cancer patients.
Lecture summary:
In this talk, I will discuss our recent work to address challenges in single-cell and spatial RNA-seq data analysis. Specific topics include pre-processing and normalization in droplet-based single-cell RNA-seq studies. I will also discuss challenges unique to spatial RNA-seq experiments with specific focus on data from the Visium10x Genomics platform.
