BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:Computational Challenges in Single-Cell Genomics - Confounding Fac
 tors\, Cell Types and Spatial Transcriptomics
DTSTART:20141006T121500
DTSTAMP:20260407T101148Z
UID:e7da713d2b6f6b1716d55e4d7c2cdd5ddc4ebc96797c7f1363785b39
CATEGORIES:Conferences - Seminars
DESCRIPTION:John C. Marioni\, PhD\, European Bioinformatics Institute (EBI
 -EMBL) and Wellcome Trust Sanger Institute\, Cambridge (UK)\nBIOENGINEERIN
 G SEMINARAbstract:\nRecent technical developments have enabled the transcr
 iptomes of thousands of cells to be assayed in an unbiased manner. These a
 pproaches have enabled heterogeneity in gene expression levels across popu
 lations of cells to be characterized as well as facilitating the identific
 ation of new\, and potentially physiologically relevant\, sub-populations 
 of cells.\nHowever\, to fully exploit such data and to answer these questi
 ons\, it is necessary to develop robust computational methods that take ac
 count of both technical noise and underlying\, potentially confounding\, v
 ariables such as the cell cycle.\nIn this presentation I will begin by bri
 efly describing how we used spike-ins to quantify technical noise in singl
 e-cell RNA-seq data\, thus facilitating identification of genes with more 
 variation in expression levels across cells than expected by chance. Subse
 quently\, I will discuss a computational approach that uses latent variabl
 e models to account for potentially confounding factors such as the cell c
 ycle before applying it to study the differentiation of Th2 cells. I will 
 show that accounting for cell-to-cell correlations due to the cell cycle a
 llows identification of otherwise obscured sub-populations of cells that c
 orrespond to different stages along the path to fully differentiated Th2 c
 ells.\nFinally\, I will describe how understanding cell type identity in a
  multicellular organism requires the integration of each cell’s expressi
 on profile with its spatial location within the tissue under study. I will
  describe a high-throughput method that combines in vitro single-cell RNA-
 sequencing with a gene expression atlas to map single cells to their locat
 ion within the tissue of interest. The utility of the method will be demon
 strated by applying it to allocate cells to their precise location within 
 the brain of the marine annelid Platynereis dumerilii.Bio:\nPhD in Applied
  Mathematics\, University of Cambridge (2008)\, then Postdoctoral research
  in the Department of Human Genetics\, University of Chicago.\nAt EBI-EMBL
  since September 2010.
LOCATION:SV1717a http://map.epfl.ch/?room=sv1717a
STATUS:CONFIRMED
END:VEVENT
END:VCALENDAR