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DESCRIPTION:Reed A. Cartwright\, Arizona State University\nStudying the pro
 cess of de novo mutation from deep-sequencing of related samples is a diff
 icult task. Because de novos are rare\, artifacts generated by experimenta
 l and biological error tend to be more common than true positives. While d
 e novos can be identified through validation\, this is a slow process. In 
 order to estimate mutation rates on large datasets in an automated way\, w
 e need to develop new probabilistic models that can handle sources of fals
 e positives.\nIn this talk I will be discussing new computational methods 
 to detect de novo mutations and their application to three different syste
 ms: human trios\, ciliate mutation accumulation experiments\, and yellow b
 ox eucalyptus.\n\nTIC Techniques In Computational Genomics\n\nA community 
 of researchers engaged in\, or dependent on\, computational analysis of ge
 nomic data\nWeekly seminars by volunteers\nDrop-in sessions/round-table di
 scussions convened by the Genome Discovery Unit (GDU)\nVenue alternates be
 tween JCSMR and RSB\, ANU.\nTo be added to TIC email list please contact m
 arcin.adamski@anu.edu.au\n
SUMMARY:Detecting Mutations with Short-Read Sequencing
URL;VALUE=URI:http://biology.anu.edu.au/news-events/tic-seminar-series-dete
 cting-mutations-short-read-sequencing
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