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SUMMARY:Microbiome\, Metagenomics and High-dimensional Compositional Data 
 Analysis - Li\, H (University of Pennsylvania )
DTSTART:20140328T093000Z
DTEND:20140328T101500Z
UID:TALK51682@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Next-generation sequencing technologies allow 16S ribosomal RN
 A gene surveys or whole metagenome shotgun sequencing in order to characte
 rize taxonomic and functional compositions of gut microbiomes. The outputs
  from such studies are short sequence reads derived from a mixture of geno
 mes of different species in a given microbial community. We first present 
 a brief overview of the statistical methods we used for 16S rRNA data anal
 ysis. We then introduce a multi-sample model-based method to quantify the 
 bacterial compositions based on shotgun metagenomics using species-specifi
 c marker genes. The resulting data are high-dimensional compositional data
 \, which complicate many of the downstream analyses. We introduce the GLMs
  with linear constraint on regression parameters in order to identify the 
 bacterial taxa that are associated clinical outcomes and a composition-adj
 usted thresholding procedure to estimate correlation network from composit
 ional data. We demonstrate the met hods using two on-going gut microbiome 
 studies at the University of Pennsylvania.\n
LOCATION:Seminar Room 1\, Newton Institute
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