Judith and David Coffey Seminar Series: Prof Matthew Ritchie (WEHI)

Abstract: Sequencing-based Spatial Transcriptomics (sST) allows gene expression to be
measured within complex tissue contexts.  Although a wide array of sST technologies are
currently available to researchers, efforts to comprehensively benchmark different
platforms are currently lacking.  The inherent variability across technologies and
datasets poses challenges in formulating standardized evaluation metrics.  To address
this, we established a collection of reference tissues and regions characterized by
well-defined histological architecture and other biological ground truth and used them
to generate the cadasSTre and SpatialBench datasets that compare 11 sST methods.  We
highlight molecular diffusion as a variable parameter across different methods and
tissues, significantly impacting the effective resolution.  Furthermore, we observed
that spatial transcriptomic data demonstrate unique attributes beyond merely adding a
spatial axis to single-cell data, including an enhanced ability to capture patterned
rare cell states along with specific markers, albeit being influenced by multiple
factors including sequencing depth and resolution.  For the 10X Visium platform, we
benchmarked the performance of different sample handling approaches after preprocessing,
explored spatially variable gene detection and the ability of clustering and cell
deconvolution to identify expected cell types and tissue regions.  Multi-sample
differential expression analysis was able to recover known gene signatures related to
biological sex or gene knockout.  Our datasets and analyses serve as a practical guide
for sST users and will be useful in future benchmarking studies.  

About the speaker: Professor Matt Ritchie has been at lab head at the WEHI for the past
11 years.  His team develops analysis methods and open-source software tailored to new
applications of genomic technology in biomedical research.  In the single-cell and
spatial biology field, this work includes tools for data preprocessing (scPipe),
benchmarking at scale (CellBench) and new protocols and analysis methods (FLAMES) for
applying long-read sequencing to single-cell research.  His most recent research is on
developing benchmarking resources for sequencing-based spatial transcriptomics
technologies (cadasSTre and SpatialBench).  Matt completed his PhD on microarray data
analysis at WEHI in 2005 under the supervision of Professor Gordon Smyth, which was
followed by a period of post-doctoral research at the EBI (Hinxton, UK) and University
of Cambridge before returning to WEHI as a Senior Research Officer in 2008.  He is a
keen advocate of open-source software, having served on both the Technical Advisory
Board and Community Advisory Board of the Bioconductor project.  

This event will be held in person and online.  

Venue: Charles Perkins Centre, Seminar Room 1.1 

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