Presentation abstract will be published shortly.
Presented with Dr Shila Ghazanfar, Cancer Research UK Cambridge Institute
In this workshop, we will focus on the bleeding edge of single-cell genomics, discussing some of the pitfalls and roadblocks that afflict many analyses. We will begin by highlighting some of the analysis steps that we find the most challenging and time-consuming and outline some things to be aware of that might indicate good or poor performance. Attendees will be encouraged to consider what analytical challenges they face in single-cell analyses and, ideally, to share with the group how they typically overcome these challenges.
Keywords: statistics; transcriptomics; normalisation; data integration; mean-variance effects
Requirements: Good knowledge and experience of analysing large-scale and complex genomics datasets.
Relevance: This workshop is relevant to those who want additional hints and tips about the analyses of large and complex genomics datasets. It is ideally suited for those familiar with R / Bioconductor and state-of-the-art analyses approaches.
Research Group Leader, Computational and Evolutionary Genomics, EMBL-EBI
John Marioni obtained his PhD in Applied Mathematics in the University of Cambridge in 2008 and did his postdoctoral research in the Department of Human Genetics, University of Chicago. He joined EMBL-EBI as Research Group Leader in Computational and Evolutionary Genomics in 2010. His group develops the computational and statistical tools necessary to exploit high-throughput genomics data, with the aim of understanding the regulation of gene expression and modelling developmental and evolutionary processes. Within this context, the Marioni group focuses on understanding how the divergence of gene expression levels is regulated, using gene expression as a definition of the molecular fingerprint of individual cells to study the evolution of cell types, and modelling spatial variability in gene-expression levels within a tissue or organism. These three strands of research are brought together by single-cell sequencing technologies. John has a joint appointment at the Wellcome Trust Sanger Institute and the Cancer Research UK Cambridge Institute, which is part of the University of Cambridge.