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DTSTAMP:20260411T085006Z
DESCRIPTION:'Combining genomics data to predict function of the non-coding 
 genome'\n\nSara Mostafavi\, University of British Columbia\n	Tuesday Septem
 ber 17\, 12-1pm\n	McIntyre Building\, Room 1034\n\nAbstract: The recent ava
 ilability of diverse genome-wide assays\, including ATAC-Seq\, ChIP-Seq\, 
 and RNA-Seq\, now enables researchers to quantify\, at a high resolution\,
  the cellular and context-specific activity of every segment of DNA. Combi
 ning genetic data with these other genomics assays provide an opportunity 
 to a) decode DNA\, for example by inferring the sequence code underlying f
 unctional differences between cell types within an individual\, and b) pre
 dict the impact of variation in a given base of DNA on cellular function. 
 However\, interpreting this data to extract biological insights requires d
 isentangling meaningful\, and hence reproducible and consequential associa
 tions\, from mere correlations (i.e. spurious associations). In this talk\
 , I will present statistical and machine learning approaches for integrati
 ng heterogeneous data\, in order to find robust associations. First\, focu
 sing on the task of finding associations between genetic variation and cel
 lular (expression) traits in a population-based study\, I will review meth
 ods for inferring and accounting for hidden confounding factors and then w
 ill describe new approaches based on latent variable modeling to infer con
 text-specific associations. Second\, I’ll describe our efforts in using de
 ep learning approaches for combining genetic and ATAC-Seq data across a la
 rge set of immune cells to learn non-coding motifs across the genome.\n
DTSTART:20190917T160000Z
DTEND:20190917T170000Z
LOCATION:Room 1034\, McIntyre Medical Building\, CA\, QC\, Montreal\, H3G 1
 Y6\, 3655 promenade Sir William Osler
SUMMARY:QLS Seminar Series - Sara Mostafavi
URL:https://www.mcgill.ca/qls/channels/event/qls-seminar-series-sara-mostaf
 avi-300180
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