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SUMMARY:Inferring Mixed Viral Populations - Greenman\, C (The Genome Analy
 sis Centre)
DTSTART:20140327T160000Z
DTEND:20140327T163000Z
UID:TALK51660@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:Any growing population of RNA viruses will undergo processes o
 f mutation and selection resulting in a mixed population of viral particle
 s. High throughput sequencing of a viral population subsequently contains 
 a mixed signal of the underlying haplotypes that need identifying. We util
 ize a pigeon-hole principle to extract haplotype information\, estimate th
 e prevalence of underlying clones\, and examine the evolutionary structure
 . The method utilises both linkage information from paired reads and depth
  information. The method utilises tree-like and recombination network evol
 ution structures and has best applicability to time series data sets of hi
 gh prevalence mutations within viral segments. Daily data from influenza a
 re used to highlight the method\, where both recombination within segments
  and re-assortment between segments are observed.\n
LOCATION:Seminar Room 1\, Newton Institute
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