Bioinformatics Seminar
Time:
Venue: Na
17 December 2019
NaOn differential discovery in high-dimensional cytometry and scRNA-seq data
Helena CrowellUniversity 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.