Jean Fan: Computational Tools for Spatially Resolved Transcriptomic Data Analysis
Channel: NorthWestBiomathsDataScienceSeminars
Date: 2022-01-21

North West Seminar Series of Mathematical Biology and Data Science 

Monday, 17th January 2022 (hosted by Mudassar Iqbal) 

https://www.cms.livjm.ac.uk/APMSeminar/

Abstract:
Characterizing cells and their transcriptional states in their spatial context is important for understanding tissue function. To enable such spatially resolved transcriptomic profiling of fixed cells in tissues, recent advances in imaging technologies have enabled high-throughput in situ, targeted transcriptomic profiling of pre-selected RNAs at molecular and single-cell resolution. Similarly, technologies based on spatially resolved RNA capture followed by sequencing have enabled non-targeted, genome-wide transcriptional profiling at the multi-cellular pixel resolution. Such spatially resolved transcriptomics data demand new computational methods to take advantage of this new spatial dimension of information to derive relevant biological insights. Here, I will describe a few recent computational approaches developed in my lab for analyzing spatially resolved transcriptomics data. Overall, we anticipate that such spatially resolved transcriptome profiling technologies coupled with spatial computational analyses could help address a wide array of questions and contribute important fundamental biological insights regarding how tissues are organized in both the healthy and diseased settings.