Bioinformatics Seminars

Current Bioinformatics Seminar

17 December 2019

On differential discovery in high-dimensional cytometry and scRNA-seq data

Helena Crowell
University of Zurich

Mass cytometry (CyTOF) allows for examination of dozens of proteins at single-cell resolution. By employing heavy metal isotopes rather than fluorescent tags, thereby significantly reducing spectral overlap, CyTOF enables generation of high-throughput high-dimensional cytometry data.

Given the emergence of replicated multi-condition experiments, a primary task in the analysis of any type of single-cell data is to make sample-level inferences, in order to identify i) differentially abundant subpopulations; and, ii) changes in expression at the subpopulation-level, i.e., differential states (DS), across conditions. Preceding such analyses, key challenges lie in data preprocessing (e.g., to remove artefactual signal), clustering (to define subpopulations), and dimension reduction.

In this talk, I will present a suite of tools for differential discovery in CyTOF data, including 'CATALYST' for preprocessing and visualization, 'diffcyt' for differential testing, and a comprehensive analysis pipeline that leverages R/Bioconductor infrastructure. Secondly, I will cover benchmarks of key analysis steps, such as clustering and dimension reduction. Finally, I will touch on how we transferred our DS analysis framework to scRNA-seq, and developed a complex, flexible simulation framework for method comparison, with the 'muscat' package.


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