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SUMMARY:Identification of enriched regions in ChIP-seq and whole-genome se
 quencing data - Park\, P (Harvard University)
DTSTART:20100716T113000Z
DTEND:20100716T120000Z
UID:TALK25514@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:An important statistical problem in analysis of ChIP-seq data 
 is robust identification of both sharp peaks (e.g.\, for transcription fac
 tors) and broad regions (e.g.\, for many histone modifications) in the enr
 ichment profile. I will describe a method based on model selection by maxi
 mum likelihood. This method is intuitive\, fast\, and can be extended easi
 ly to multi-sample cases. This method is also applicable to detection of c
 opy number variations from whole-genome sequencing data. I will illustrate
  the applications of this method with examples from the Encyclopedia of DN
 A Elements (ENCODE) and the Cancer Genome Atlas (TCGA) data. 
LOCATION:Seminar Room 1\, Newton Institute
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