In this talk, based on specific brain cancer results published in 2019, Dr. Gordon will outline some of the challenges encountered working with existing public single-cell data sets to perform cell type labelling and differential gene expression analysis. In particular, he will show how coupling R/Bioconductor analysis with IPA helped support a pro-inflammatory mutant hypothesis establish via flow cytometry (FC) and immunohistochemstry (IHC) markers. Furthermore, unlike the FC and IHC data, the single cell analysis distinguished the mechanism of the inflammatory response as microglia-driven rather than macrophage-driven.

Paul Gordon, PhD is the Bioinformatics Manager for the Cumming School of Medicine's Centre for Health Genomics and Informatics. Dr. Gordon has a background in Computer Science, but has been applying it to the field of molecular biology since 1996 with primer design and gene analysis of the first archaeal genome, Sulfolobus solfataricus, by Sanger sequencing. Since then he has worked on a number of Genome Canada projects ranging from biofuel enzyme discovery, to crop genetics, to kidney transplant monitoring. In these projects he has contributed to the parallelization of microarray analysis in R/Bioconductor, and co-authored more than 50 journal papers, including several using Next Generation Sequencing for clinical research from his current role.