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SUMMARY:Linking taxa to function through contig clustering of microbial me
 tagenomes - Quince\, C (University of Glasgow)
DTSTART:20140328T134500Z
DTEND:20140328T143000Z
UID:TALK51679@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Co-authors: Johannes Alneberg (KTH Royal Institute of Technolo
 gy\, Stockholm\, Sweden)\, Brynjar Smaari Bjarnason (KTH Royal Institute o
 f Technology\, Stockholm\, Sweden)\, Ino de Bruijn (KTH Royal Institute of
  Technology\, Stockholm\, Sweden)\, Melanie Schirmer (University of Glasgo
 w)\, Joshua Quick (University of Birmingham)\, Nicholas J. Loman (Universi
 ty of Birmingham)\, Anders F. Andersson (KTH Royal Institute of Technology
 \, Stockholm\, Sweden)\, Konstantinos Gerasimidis (University of Glasgow) 
 \n\nTaxonomic profiling of microbial communities can answer the question o
 f Who is there? This can be achieved either through marker gene sequencing
  or true shotgun metagenomics. The latter because the functional genes of 
 all community members are sequenced allows us to answer the additional que
 stion: What are they doing? However\, there is a third question that is ke
 y to understanding microbial communities: Who is doing what? This question
  has received much less attention because to answer it requires the extrac
 tion of complete genomes from metagenomes. Assembly of metagenomes can gen
 erate millions of contigs\, assembled genome fragments\, with no informati
 on on which contig derives from which genome. Here I will present CONCOCT\
 , a novel algorithm that combines sequence composition\, coverage across m
 ultiple samples\, and read-pair linkage to automatically cluster contigs i
 nto genomes. CONCOCT uses a dimensionality reduction coupled to a Gaus sia
 n mixture model\, fit using a variational Bayesian algorithm which automat
 ically identifies the optimal number of clusters. We demonstrate high reca
 ll and precision rates on artificial as well as real human gut metagenome 
 datasets. Linking contigs into genome clusters\, allows the frequencies of
  those clusters to be related to metadata\, revealing function. We apply t
 his approach to fecal metagenomes obtained from the E. coli O104:H4 epidem
 ic (Germany\, 2011) and are able to directly extract the outbreak genome. 
 We also use it to identify organisms associated with inflammation in sampl
 es from children with Crohns disease. \n\nRelated Links\n\nhttp://arxiv.or
 g/abs/1312.4038 - arXiv preprint \n
LOCATION:Seminar Room 1\, Newton Institute
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